Cost
$5.98per task
Cost per task. One Intelligence Index task at list price, every token counted. Run at max effort.
- Cached input
- $0.20 per 1M tokens
Claude Opus model by Anthropic
Claude Opus 5.5
A Claude Opus release for complex agentic, coding, and professional work.
Where it sits in Anthropic's lineup
- Claude HaikuAnthropic's small, fast Claude model family for high-volume, latency-sensitive work.Claude Haiku 5.5
- Claude SonnetAnthropic's balanced Claude model family.Claude Sonnet 5.5
- Claude OpusAnthropic's high-capability Claude model family.This model
- Claude FableAnthropic's Claude family for demanding reasoning and long-horizon agentic work.Claude Fable 5.1
- Stack role
- Foundation Model / Reasoning Engine
- Offered in
- 9 products
- Made by
- Anthropic
- Family
- Claude Opus, version 5.5
- Released
- Sep 22, 2026 Current
- In its family
- The newest of 6 Claude Opus releases.
Strengths and weaknesses
Compare with other models Up to 3 beside Claude Opus 5.5
- Claude Opus 5.5
Suggested comparisons
The models a buyer weighs against Claude Opus 5.5, picked on list price and on Artificial Analysis's Intelligence Index of overall quality. Add one to draw it beside Claude Opus 5.5.
Claude Opus 5.5
Among the 40 current releases on this chart, Claude Opus 5.5 ranks first of 38 on Hard reasoning, first of 37 on Code and first of 31 on Agentic coding. Computer use is Anthropic's own figure on OSWorld 2.1, marked on the chart. It ranks lowest on Science, 19th of 24. Instruction following: not yet published by Anthropic or any independent evaluator, checked Nov 2, 2026.
Each axis is one public benchmark at one setting, on its own fixed 0 to 100 scale, so adding a model never moves another. A dotted bridge crosses a missing result, which is never a zero. A hollow mark is a result from another source: the maker's own figure or another lab's run, where the benchmark's usual source has not tested the model yet. The readout names it.
On the chart
- Claude Opus 5.5This pageResults on 11 of 12 axes$4 / $2098 tokens/sFirst token in 700 s
Prices and speeds read between Oct 26, 2026 and Oct 28, 2026.
Claude Opus 5.5 on each axis11 of 12 with a result
The share of Terminal-Bench 4.0's long terminal tasks the model finishes on its own: services, kernels, proofs and data pipelines, graded on the final artifact with no partial credit.
Terminal-Bench 4.0, pass@1 averaged over 3 runs, mini-swe-agent harness
- Claude Opus 5.565.2%Vals.ai ranked it 1st on its leaderboard of Oct 24, 2026.
The share of SciCode's scientific programming subproblems the model's code solves on the first attempt.
SciCode, subproblem accuracy, pass@1, highest effort run
- Claude Opus 5.566.9%Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on.
The share of FrontierMath's held-out research-grade problems (tiers 1 to 3) the model answers correctly.
FrontierMath Tiers 1-3, accuracy, pass@1, highest effort run
- Claude Opus 5.591.2%
The share of GPQA Diamond's graduate-level biology, chemistry and physics questions the model answers correctly.
GPQA Diamond, accuracy, pass@1, highest effort run
- Claude Opus 5.590.6%
The share of Humanity's Last Exam's 2,158 text-only questions, expert-written at the edge of human knowledge, the model answers correctly without tools.
Humanity's Last Exam, accuracy, text-only questions, no tools
- Claude Opus 5.561.4%Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on.
The share of each AutomationBench task's objectives the model completes by calling REST APIs across simulated business apps (Gmail, Sheets, Slack, Salesforce, Zendesk, Jira, HubSpot), averaged over tasks. A task that breaks one of its policy guardrails scores zero.
AutomationBench-AA, score, Artificial Analysis run
- Claude Opus 5.569.5%Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on.
How much of each OSWorld 2.1 workflow the model completes by operating a real Ubuntu desktop through screenshots, mouse and keyboard: all 108 long tasks across apps, files, mail and browsers, on the September 2026 v2.1 release of the task files. A point is the mean share of each task's weighted checks the model passes (the partial score, as a percentage). The OSWorld team's own runs come first. Where the team has not run a release, the point is another lab's run or the maker's own published figure, marked with who ran it and the benchmark it ran: OSWorld 2.1 in the maker's harness, OSWorld 2.0's offline set or the earlier OSWorld-Verified. Those points are drawn so the release has a figure, and they are not ranked against the team's runs.
OSWorld 2.1, partial score, full 108-task set, v2.1 release
- Claude Opus 5.581.8%reported by AnthropicAnthropic's own run at max effort in its computer-use harness, averaged over five runs. It fully completed 48.7% of the tasks.
The share of AA-LCR's questions the model answers correctly by reasoning across long sets of real documents, about 100K tokens each.
AA-LCR v1.1, accuracy, Artificial Analysis run
- Claude Opus 5.584.7%Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on.
The share of MMMU-Pro's college-level questions over charts, diagrams and photos the model answers correctly.
MMMU-Pro, overall accuracy, no tools
- Claude Opus 5.587.7%Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on.
The share of AA-Omniscience's 6,000 knowledge questions across 42 economically relevant topics the model answers correctly from memory, without search.
AA-Omniscience Accuracy, accuracy, Artificial Analysis run
- Claude Opus 5.565.5%Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on.Hallucination rate 50.3% in the same run (lower is better)
The share of SpeechMap's 2,120 sensitive and controversial but legal requests the model answers in full: arguments, essays and explanations on contested themes in politics, religion, race, sex, history and similar topics, four wordings per theme across 530 themes. SpeechMap's judge rates each response complete, evasive (hedged or redirected), a denial, or an error (the provider's API blocked the request). Only complete answers count, so the point is the share answered in full: 100 minus the share hedged, refused or blocked by the provider. Higher means more lawful requests answered in full. The share blocked at the provider is printed apart in the table, because an API error is not the model declining. Where SpeechMap runs a release both with reasoning off and with reasoning on (a -reasoning or -thinking entry), the reasoning-on entry is used; a release with one entry uses that entry.
SpeechMap, % Complete over 2,120 contested requests, reasoning-on entry
- Claude Opus 5.582.8%SpeechMap tested it through OpenRouter at medium thinking and counted 12.7% of requests denied and 2.2% evaded. Another 2.3% failed at the provider and count against the score.2.3% of requests failed at the provider and count against it
The share of MultiChallenge's multi-turn conversations in which the model keeps every instruction it was given earlier in the conversation.
MultiChallenge, accuracy, Scale AI run
- Claude Opus 5.5Not yet published by Anthropic or any independent evaluator, checked Nov 2, 2026
Cost, speed, capacity, quality and accuracy for Claude Opus 5.5, with where each figure sits among the 40 models GILD tracks. These measures stand beside the chart and never feed it.
Speed
98tokens a second
Output speed. How fast it writes once the answer starts. Run at max effort.
- First token
- 712 s
- Whole answer
- 717 s
Capacity
1Mtokens
Context window. The most one request can hold, as the maker states it.
- Max output
- 128K
- Reads
- Text, Images
Quality
57.6of 100
Intelligence Index. One composite score across independent evaluations. Run at max effort.
- GDPval knowledge work
- 1,866 Elo
- Terminal-Bench 4.0
- 59.6%
- Epoch Capabilities Index
- 169
Hallucination
50.3%wrong when it should say “I don’t know”
Hallucination rate. Of the questions it can't get right, how often it answers anyway. Lower is better. Run at max effort.
- Knowledge accuracy
- 65.5%
Where you can get it
15of 19 routes
Routes offering it. Of the clouds, gateways and coding products GILD tracks, those offering it today.
- Open weights
- No
- Licence
- Commercial Terms of Service
Figures from Artificial Analysis, Anthropic, OpenRouter, Epoch AI and GILD's route matrix, read Oct 26 to Nov 1, 2026. Each measure's definition and source open under .
Every value with its benchmark, run and source
| Axis | Benchmark and setting | Claude Opus 5.5 | Run | Source | Date |
|---|---|---|---|---|---|
| Agentic coding | Terminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness. Vals.ai ranked it 1st on its leaderboard of Oct 24, 2026. | 65.2% | Claude Opus 5.5Effort: not published. Harness: mini-swe-agent. | Vals.ai | Oct 24, 2026 |
| Code | SciCodeSubproblem accuracy, pass@1, highest effort run. Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on. | 66.9% | Claude Opus 5.5 (Max, Default Fallback)Effort: max. Harness: none.Run as Anthropic serves it by default: requests its safeguards stop are answered by a fallback model. | Artificial Analysis | Oct 28, 2026 |
| Math | FrontierMath Tiers 1-3Accuracy, pass@1, highest effort run | 91.2% | Effort: max. Harness: none. | Epoch AI | Sep 22, 2026 |
| Science | GPQA DiamondAccuracy, pass@1, highest effort run | 90.6% | Effort: max. Harness: none. | Epoch AI | Sep 22, 2026 |
| Hard reasoning | Humanity's Last ExamAccuracy, text-only questions, no tools. Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on. | 61.4% | Claude Opus 5.5 (Max, Default Fallback)Effort: max. Harness: none.Run as Anthropic serves it by default: requests its safeguards stop are answered by a fallback model. | Artificial Analysis | Oct 28, 2026 |
| Tool use | AutomationBench-AAScore, Artificial Analysis run. Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on. | 69.5% | Claude Opus 5.5 (Max, Default Fallback)Effort: max. Harness: Artificial Analysis AutomationBench harness.Run as Anthropic serves it by default: requests its safeguards stop are answered by a fallback model. | Artificial Analysis | Oct 28, 2026 |
| Computer use | OSWorld 2.1Partial score, full 108-task set, v2.1 release. Anthropic's own run at max effort in its computer-use harness, averaged over five runs. It fully completed 48.7% of the tasks. | 81.8% | Claude Opus 5.5 (max)Effort: max. Harness: Anthropic computer-use harness.Not drawn: Anthropic 87.2% in its maker's own harness, Oct 7, 2026. Source | AnthropicReported by Anthropic | Sep 22, 2026 |
| Long context | AA-LCR v1.1Accuracy, Artificial Analysis run. Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on. | 84.7% | Claude Opus 5.5 (Max, Default Fallback)Effort: max. Harness: none.Run as Anthropic serves it by default: requests its safeguards stop are answered by a fallback model. | Artificial Analysis | Oct 28, 2026 |
| Multimodal | MMMU-ProOverall accuracy, no tools. Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on. | 87.7% | Claude Opus 5.5 (Max, Default Fallback)Effort: max. Harness: none.Run as Anthropic serves it by default: requests its safeguards stop are answered by a fallback model. | Artificial Analysis | Oct 28, 2026 |
| Factuality | AA-Omniscience AccuracyAccuracy, Artificial Analysis run. Artificial Analysis tested Opus 5.5 as Anthropic serves it by default, with its safeguard fallback model on. | 65.5%Hallucination rate 50.3% in the same run (lower is better) | Claude Opus 5.5 (Max, Default Fallback)Effort: max. Harness: none.Run as Anthropic serves it by default: requests its safeguards stop are answered by a fallback model. | Artificial Analysis | Oct 28, 2026 |
| Answers in full | SpeechMap% Complete over 2,120 contested requests, reasoning-on entry. SpeechMap tested it through OpenRouter at medium thinking and counted 12.7% of requests denied and 2.2% evaded. Another 2.3% failed at the provider and count against the score. | 82.8%2.3% of requests failed at the provider and count against it | Effort: medium. Harness: none. | SpeechMap.AI | Oct 27, 2026 |
| Instruction following | MultiChallengeAccuracy, Scale AI run | Not yet published by Anthropic or any independent evaluator, checked Nov 2, 2026 |
Price and speed
- Claude Opus 5.5 lists at $4 per million input tokens and $20 per million output tokens. Anthropic pricing, Oct 26, 2026.
- Claude Opus 5.5, at max effort, writes 98.4 output tokens per second on Anthropic's API, and its first token arrives 700 s after the request. Artificial Analysis, Oct 28, 2026.
- Fastest on the chart is the shortest time to a 500-token answer: time to first token plus 500 tokens at the median output speed.
Every model with a result, axis by axis
57 models. A maker's own figure and another lab's run are marked with their benchmark; a missing result reads "Not yet published", never zero.
| Model | Agentic coding | Code | Math | Science | Hard reasoning | Tool use | Computer use | Long context | Multimodal | Factuality | Answers in full | Instructions |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Claude Opus 5.5 | 65.2% | 66.9% | 91.2% | 90.6% | 61.4% | 69.5% | 81.8%Reported by Anthropic | 84.7% | 87.7% | 65.5% | 82.8% | Not yet published |
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| Claude Haiku 5.5 | 36.4% | 55% | 75.1% | 89.6% | 44.4% | 35.4% | 72.4%Reported by AnthropicOSWorld 2.1 | 82.7% | Not yet published | 34.7% | 78.8% | 67.7% |
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| Claude Sonnet 5.5 | 64.1% | 61% | 88.8% | 95.6% | 55% | 71.8% | 80.1%Reported by Anthropic | 82.7% | Not yet published | 51.5% | 81.6% | Not yet published |
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| Claude Fable 5.1 | 58.1% | 63.1% | 90.2% | 93.4%Run by Vals.ai | 59.1% | 59.4% | 80.7%Reported by Anthropic | 85.3% | 86.3%Run by Moonshot AI | 68.4% | 72.4% | Not yet published |
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| Claude Opus 5 | 53.5% | 56.4% | 85.6% | 93.9% | 54.9% | 56.6% | 77.7% | 79.3% | 84.7% | 60.9% | 73.7% | Not yet published |
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| Claude Sonnet 5 | 10.6% | 54.3% | 65.6% | 80.3% | 41.3% | 36.5% | 57%Reported by Anthropic | 82% | 77.3% | 40.1% | Not yet published | Not yet published |
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| Claude Fable 5 | 41.4% | 61% | 87% | 85.9% | 55.5% | 54.1% | Not yet published | 82.3% | Not yet published | 65.4% | 64.8% | 63.5%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.8 | 23.2% | 54.4% | 80% | 91% | 48.7% | 45.6% | 54.8%Run by OSWorld teamOSWorld 2.0 | 77.7% | Not yet published | 48.8% | 67.4% | 62.2%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.7 | Not yet published | 54.5% | 70.2% | 86.4% | 42.3% | Not yet published | 48.9%Run by OSWorld teamOSWorld 2.0 | 78.7% | 78.8% | 48.9% | 70.2% | 58.6%Run by Artificial AnalysisIFBench |
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| Claude Sonnet 4.6 | 3%Run by Artificial AnalysisTerminal-Bench 4.0 | 50.1% | 71.1%Run by Epoch AIOTIS Mock AIME 2024-2025 | 78.8% | 33.6% | 20.1% | 41.5%Run by OSWorld teamOSWorld 2.0 | 80% | 73.3% | 40.9% | 35.8% | 56.6%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.6 | Not yet published | Not yet published | 66% | 88.4% | 39.9% | Not yet published | Not yet published | 78% | 75.4% | 47% | 59.9% | 37.2% |
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| Claude Opus 4.5 | Not yet published | Not yet published | 34.4% | 86% | 30.1% | Not yet published | Not yet published | 77.3% | 74% | 46.6% | 57.5% | 59% |
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| Claude Haiku 4.5 | Not yet published | 42.2% | 66.7%Run by Epoch AIOTIS Mock AIME 2024-2025 | 71.2% | 10.4% | 3.2% | Not yet published | 74.3% | 58.6% | 18% | 24.7% | 50.5% |
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| Claude Sonnet 4.5 | Not yet published | 45.7% | 23.9% | 82.3% | 17.8% | 14.1% | Not yet published | 72.3% | 68.7% | 32.9% | 31.4% | 55.3% |
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| GPT-6.1 Terra | 49.5% | 55.1% | 90.9% | 94.3% | 46.2% | 60.2% | 74.2%Reported by OpenAIOSWorld 2.1 | 82.7% | 84.7% | 47.6% | Not yet published | 74.2% |
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| GPT-6.1 Sol | 55.1% | 54.2% | 93.7% | 95.4% | 52.9% | 64.9% | 78%Reported by OpenAIOSWorld 2.1 | 83% | 86% | 61.8% | 69.5% | 82% |
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| GPT-6 Luna | 13.6% | 54.6% | 78.9% | 90.5% | 38.5% | 53.2% | 48.9%Run by AnthropicOSWorld 2.1 | 83.3% | 79.7% | 39.6% | 63.4% | Not yet published |
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| GPT-6 Astra | 59.6% | 56.5% | 93.7% | 95.8% | 54.7% | 68.5% | 75.8%Run by Meta | 80.7% | 86.9% | 61.6% | 68.2% | Not yet published |
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| GPT-5.6 Sol | 37.9% | 57.1% | 89.1% | 93.5% | 49.5% | 60.1% | 62.7%Run by OSWorld teamOSWorld 2.0 | 84% | 83.4% | 69.7%Run by Epoch AISimpleQA Verified | Not yet published | 72.7%Run by Artificial AnalysisIFBench |
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| GPT-5.6 Terra | 22.7% | 55% | 86% | 93.3% | 42.9% | 59.6% | Not yet published | 83% | 80.7% | 42.3% | Not yet published | 71.2%Run by Artificial AnalysisIFBench |
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| GPT-5.6 Luna | 11.6% | 53.6% | 82.1% | 91.6% | 39.5% | 50.2% | Not yet published | 83.7% | 78.6% | 41%Run by Epoch AISimpleQA Verified | Not yet published | Not yet published |
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| GPT-5.5 | 14.6%Run by Artificial AnalysisTerminal-Bench 4.0 | 55.8% | 85.3% | 93.5%Run by Artificial Analysis | 45.8% | 47.3% | 49.5%Run by OSWorld teamOSWorld 2.0 | 84.3% | 79.9% | 63%Run by Epoch AISimpleQA Verified | Not yet published | 75.9%Run by Artificial AnalysisIFBench |
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| GPT-5.4 | Not yet published | Not yet published | 78.6% | 93.3% | 43.7% | Not yet published | Not yet published | 82% | 78.4% | Not yet published | Not yet published | 73.9%Run by Artificial AnalysisIFBench |
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| gpt-oss-120b | 14.2%Run by Terminal-Bench (via Epoch AI)Terminal-Bench 2.0 | 34% | 88.9%Run by Epoch AIOTIS Mock AIME 2024-2025 | 75.8% | 19.6% | 0.2% | Not yet published | 52% | Not yet published | 16.8%Reported by OpenAISimpleQA | 36.3% | 45.3% |
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| GPT-6 Sol | 44.4% | 57.6% | 89.8% | 94.3% | 47.9% | 61.6% | 64.4%Reported by OpenAIOSWorld 2.0 | 83.7% | 82.9% | 54.5% | 64% | Not yet published |
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| GPT-5.3-Codex | Not yet published | Not yet published | Not yet published | 91.5%Run by Artificial Analysis | 42.5% | Not yet published | Not yet published | 83.3% | 78.5% | Not yet published | Not yet published | 75.4%Run by Artificial AnalysisIFBench |
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| Gemini 4 Argon | 57.6% | 61.8% | 86% | 96.4% | 57.1% | 77.5% | 69.2%Reported by GoogleOSWorld 2.0 | 79.7% | Not yet published | 48.3% | 87% | 78.7% |
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| Gemini 3.8 Flash | 19.7% | 56.6% | 68.4% | 95.4% | 47.8% | 59.9% | 59%Reported by GoogleOSWorld 2.0 | 81.3% | 85.6% | 50.5% | 86.1% | Not yet published |
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| Gemma 4 31B | Not yet published | 45.5% | Not yet published | 85.7%Run by Artificial AnalysisGPQA Diamond | 23.6% | 4.9% | Not yet published | 69.7% | 73.4% | 10.4%Run by Epoch AISimpleQA Verified | 82.3% | 75.6%Run by Artificial AnalysisIFBench |
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| Gemini 3.1 Pro Preview | 2.5% | 58.7% | 59.6% | 94.4% | 47% | 35.4% | Not yet published | 82% | 82.4% | 54.9% | 59.9% | 71.4% |
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| Gemini 3.6 Flash | 7.1%Run by Artificial AnalysisTerminal-Bench 4.0 | 53.4% | 58.9% | 94.1% | 40.8% | 53% | 83%Reported by GoogleOSWorld-Verified | 80% | 83.2% | 66.2%Run by Epoch AISimpleQA Verified | 87.2% | Not yet published |
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| DeepSeek V4.1 Flash | 31.8% | 55.9% | 71.2% | 93.2% | 43.3% | 66.6% | 69.3%Run by Moonshot AIOSWorld 2.1 | 82.7% | 80.6% | 39.6% | Not yet published | 74.9% |
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| DeepSeek V4 Pro | 14.1% | 51% | 64.6% | 91.7% | 41% | 56.7% | Not yet published | 80.3% | Not yet published | 45.2% | 72% | Not yet published |
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| Kimi K3.1 Pro | 63.6% | 60.8% | Not yet published | 94.2%Reported by Moonshot AI | 52.5% | 73.3% | 79.6%Reported by Moonshot AIOSWorld 2.1 | 86.3% | 83.9% | 48.9% | Not yet published | Not yet published |
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| Kimi K3 | 17.2% | 59.5% | 72.2% | 93.1% | 46.9% | 58.3% | Not yet published | 88.7% | 80.5% | 50.6%Run by Epoch AISimpleQA Verified | 65.9% | Not yet published |
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| Kimi K2.7 Code | 1%Run by Artificial AnalysisTerminal-Bench 4.0 | 47.8% | 54% | 87.9% | 35% | 24.5% | Not yet published | 79.3% | Not yet published | 36.5%Run by Epoch AISimpleQA Verified | Not yet published | 63.1%Run by Artificial AnalysisIFBench |
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| Mistral Large 4 | 24.7%Run by Artificial AnalysisTerminal-Bench 4.0 | Not yet published | Not yet published | Not yet published | Not yet published | 57.8% | Not yet published | Not yet published | Not yet published | 26% | Not yet published | Not yet published |
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| Mistral Medium 3.5 | 0%Run by Artificial AnalysisTerminal-Bench 4.0 | 40.2% | Not yet published | 74.8%Run by Artificial AnalysisGPQA Diamond | 13.8% | 6.3% | Not yet published | 69.3% | 64.9% | 23% | 70.5% | 68.8%Run by Artificial AnalysisIFBench |
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| Grok 4.7 | 28.8% | 57.4% | 53% | 92.7% | 43.1% | 65.6% | Not yet published | 76.7% | Not yet published | 42.7% | 64.1% | Not yet published |
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| Grok 4.6 | 17.2% | 56.5% | 66% | 93.2% | 42.9% | 66.7% | Not yet published | 80.3% | Not yet published | 48.9%Run by Epoch AISimpleQA Verified | 83.6% | Not yet published |
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| Grok 4.5 | 8.6% | 55% | 57.2% | 93.4% | 42.7% | 57.9% | Not yet published | 79.3% | 80.4% | 48.3%Run by Epoch AISimpleQA Verified | 93.1% | Not yet published |
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| MiniMax M3.1 Flash | 25.3% | 53.4% | Not yet published | Not yet published | 48% | 72.5% | 61.7%Reported by MiniMaxOSWorld 2.0 | 79.7% | 79.1% | 45.1% | Not yet published | Not yet published |
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| Mercury 3 | 3% | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published |
| GLM-5.3-Flash | 37.4% | 51.6% | 55.8% | 90.2% | 39.9% | 60.4% | 59.1%Reported by Z.aiOSWorld 2.0 | 80% | 86%Run by Vals.aiMMMU-Pro | 28.2% | 65.4% | Not yet published |
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| GLM-5.3 | 38.9% | 59% | 68.8% | 90.9% | 42.3% | 62.2% | Not yet published | 79.7% | Not yet published | 32.3% | 71.5% | Not yet published |
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| GLM-5.2 | 1%Run by Artificial AnalysisTerminal-Bench 4.0 | 51.2% | 59.2% | Not yet published | 41.1% | 28.4% | Not yet published | 78.3% | Not yet published | 34.2%Run by Epoch AISimpleQA Verified | Not yet published | 73.3%Run by Artificial AnalysisIFBench |
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| Muse Spark Open | 6.6% | 58.4% | 69.8% | 88.6% | 43.9% | 49.7% | 80.4%Reported by MetaOSWorld-Verified | 78.3% | 80.9% | 42% | Not yet published | 74.2% |
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| Muse Wonder | 49.5% | 60.3% | 82.1% | Not yet published | 50.1% | 68.1% | 72.6%Reported by Meta | 80.7% | Not yet published | 38% | 42.7% | Not yet published |
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| Muse Spark 1.3 | 10.6% | 58.8% | 74% | 93.5%Run by Artificial AnalysisGPQA Diamond | 48.7% | 57.9% | 69.6% | 83% | 82% | 38% | 25.8% | Not yet published |
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| Llama 4 Scout | Not yet published | 21.3% | 7.8%Run by Epoch AIOTIS Mock AIME 2024-2025 | 51.8% | 3.8% | 0.2% | Not yet published | 27.7% | 52.9% | Not yet published | 70.1% | 39.5%Run by Artificial AnalysisIFBench |
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| Llama 4 Maverick | Not yet published | 31.7% | 20.6%Run by Epoch AIOTIS Mock AIME 2024-2025 | 67% | 4.9% | 0.2% | Not yet published | 50% | 62.1% | Not yet published | 58.3% | 43%Run by Artificial AnalysisIFBench |
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| Qwen3.8 27B | 5.6%Run by Artificial AnalysisTerminal-Bench 4.0 | 46.6% | Not yet published | 90.5%Run by Artificial AnalysisGPQA Diamond | 33.9% | 48.2% | 84.3%Reported by AlibabaOSWorld-Verified | 82% | 76.3% | 17.3% | Not yet published | 79.5%Reported by AlibabaIFBench |
| ||||||||||||
| Qwen3.8 Max | 38.9% | 52.1% | 65.6% | 92.3% | 43.1% | 56.2% | Not yet published | 80.3% | 82.8% | 29.5% | 65.3% | Not yet published |
| ||||||||||||
| MiMo-V2.6-Pro | 31.3% | 60.9% | Not yet published | Not yet published | 49.4% | 58.6% | 82%Reported by XiaomiOSWorld-Verified | 86.3% | Not yet published | 34.8% | 66.5% | Not yet published |
| ||||||||||||
| MiMo-V2.6-Flash | 24.2% | 51.3% | Not yet published | Not yet published | 35.1% | 64.1% | 80.8%Reported by XiaomiOSWorld-Verified | 74.3% | 73.1% | 27.2% | 66.9% | Not yet published |
| ||||||||||||
| Ling 3.1 Flash | 32.8%Run by Artificial AnalysisTerminal-Bench 4.0 | 56.8% | Not yet published | Not yet published | 43.5% | 67.5% | Not yet published | 82.3% | Not yet published | 26.5% | Not yet published | Not yet published |
| ||||||||||||
| Step 5 Preview | 31.8% | 58.9% | Not yet published | 93.5%Reported by StepFunGPQA Diamond | 46.5% | 51% | Not yet published | 88.3% | 76.4% | 36.4% | 59.7% | Not yet published |
| ||||||||||||
Agentic codingTerminal-Bench 4.0
- Claude Opus 5.565.2%
- Claude Sonnet 5.564.1%
- Kimi K3.1 Pro63.6%
- GPT-6 Astra59.6%
- Claude Fable 5.158.1%
- Gemini 4 Argon57.6%
- GPT-6.1 Sol55.1%
- Claude Opus 553.5%
- GPT-6.1 Terra49.5%
- Muse Wonder49.5%
- GPT-6 Sol44.4%
- Claude Fable 541.4%
- GLM-5.338.9%
- Qwen3.8 Max38.9%
- GPT-5.6 Sol37.9%
- GLM-5.3-Flash37.4%
- Claude Haiku 5.536.4%
- DeepSeek V4.1 Flash31.8%
- Step 5 Preview31.8%
- MiMo-V2.6-Pro31.3%
- Grok 4.728.8%
- MiniMax M3.1 Flash25.3%
- MiMo-V2.6-Flash24.2%
- Claude Opus 4.823.2%
- GPT-5.6 Terra22.7%
- Gemini 3.8 Flash19.7%
- Kimi K317.2%
- Grok 4.617.2%
- DeepSeek V4 Pro14.1%
- GPT-6 Luna13.6%
- GPT-5.6 Luna11.6%
- Claude Sonnet 510.6%
- Muse Spark 1.310.6%
- Grok 4.58.6%
- Muse Spark Open6.6%
- Mercury 33%
- Gemini 3.1 Pro Preview2.5%
- Ling 3.1 Flash32.8%Artificial Analysis's run, Terminal-Bench 4.0
- Mistral Large 424.7%Artificial Analysis's run, Terminal-Bench 4.0
- GPT-5.514.6%Artificial Analysis's run, Terminal-Bench 4.0
- gpt-oss-120b14.2%Terminal-Bench's run, Terminal-Bench 2.0
- Gemini 3.6 Flash7.1%Artificial Analysis's run, Terminal-Bench 4.0
- Qwen3.8 27B5.6%Artificial Analysis's run, Terminal-Bench 4.0
- Claude Sonnet 4.63%Artificial Analysis's run, Terminal-Bench 4.0
- Kimi K2.7 Code1%Artificial Analysis's run, Terminal-Bench 4.0
- GLM-5.21%Artificial Analysis's run, Terminal-Bench 4.0
- Mistral Medium 3.50%Artificial Analysis's run, Terminal-Bench 4.0
The other models in the grid have no result on Terminal-Bench 4.0 yet.
CodeSciCode
- Claude Opus 5.566.9%
- Claude Fable 5.163.1%
- Gemini 4 Argon61.8%
- Claude Sonnet 5.561%
- Claude Fable 561%
- MiMo-V2.6-Pro60.9%
- Kimi K3.1 Pro60.8%
- Muse Wonder60.3%
- Kimi K359.5%
- GLM-5.359%
- Step 5 Preview58.9%
- Muse Spark 1.358.8%
- Gemini 3.1 Pro Preview58.7%
- Muse Spark Open58.4%
- GPT-6 Sol57.6%
- Grok 4.757.4%
- GPT-5.6 Sol57.1%
- Ling 3.1 Flash56.8%
- Gemini 3.8 Flash56.6%
- GPT-6 Astra56.5%
- Grok 4.656.5%
- Claude Opus 556.4%
- DeepSeek V4.1 Flash55.9%
- GPT-5.555.8%
- GPT-6.1 Terra55.1%
- Claude Haiku 5.555%
- GPT-5.6 Terra55%
- Grok 4.555%
- GPT-6 Luna54.6%
- Claude Opus 4.754.5%
- Claude Opus 4.854.4%
- Claude Sonnet 554.3%
- GPT-6.1 Sol54.2%
- GPT-5.6 Luna53.6%
- Gemini 3.6 Flash53.4%
- MiniMax M3.1 Flash53.4%
- Qwen3.8 Max52.1%
- GLM-5.3-Flash51.6%
- MiMo-V2.6-Flash51.3%
- GLM-5.251.2%
- DeepSeek V4 Pro51%
- Claude Sonnet 4.650.1%
- Kimi K2.7 Code47.8%
- Qwen3.8 27B46.6%
- Claude Sonnet 4.545.7%
- Gemma 4 31B45.5%
- Claude Haiku 4.542.2%
- Mistral Medium 3.540.2%
- gpt-oss-120b34%
- Llama 4 Maverick31.7%
- Llama 4 Scout21.3%
The other models in the grid have no result on SciCode yet.
MathFrontierMath Tiers 1-3
- GPT-6.1 Sol93.7%
- GPT-6 Astra93.7%
- Claude Opus 5.591.2%
- GPT-6.1 Terra90.9%
- Claude Fable 5.190.2%
- GPT-6 Sol89.8%
- GPT-5.6 Sol89.1%
- Claude Sonnet 5.588.8%
- Claude Fable 587%
- GPT-5.6 Terra86%
- Gemini 4 Argon86%
- Claude Opus 585.6%
- GPT-5.585.3%
- GPT-5.6 Luna82.1%
- Muse Wonder82.1%
- Claude Opus 4.880%
- GPT-6 Luna78.9%
- GPT-5.478.6%
- Claude Haiku 5.575.1%
- Muse Spark 1.374%
- Kimi K372.2%
- DeepSeek V4.1 Flash71.2%
- Claude Opus 4.770.2%
- Muse Spark Open69.8%
- GLM-5.368.8%
- Gemini 3.8 Flash68.4%
- Claude Opus 4.666%
- Grok 4.666%
- Claude Sonnet 565.6%
- Qwen3.8 Max65.6%
- DeepSeek V4 Pro64.6%
- Gemini 3.1 Pro Preview59.6%
- GLM-5.259.2%
- Gemini 3.6 Flash58.9%
- Grok 4.557.2%
- GLM-5.3-Flash55.8%
- Kimi K2.7 Code54%
- Grok 4.753%
- Claude Opus 4.534.4%
- Claude Sonnet 4.523.9%
- gpt-oss-120b88.9%Epoch AI's run, OTIS Mock AIME 2024-2025
- Claude Sonnet 4.671.1%Epoch AI's run, OTIS Mock AIME 2024-2025
- Claude Haiku 4.566.7%Epoch AI's run, OTIS Mock AIME 2024-2025
- Llama 4 Maverick20.6%Epoch AI's run, OTIS Mock AIME 2024-2025
- Llama 4 Scout7.8%Epoch AI's run, OTIS Mock AIME 2024-2025
The other models in the grid have no result on FrontierMath Tiers 1-3 yet.
ScienceGPQA Diamond
- Gemini 4 Argon96.4%
- GPT-6 Astra95.8%
- Claude Sonnet 5.595.6%
- GPT-6.1 Sol95.4%
- Gemini 3.8 Flash95.4%
- Gemini 3.1 Pro Preview94.4%
- GPT-6.1 Terra94.3%
- GPT-6 Sol94.3%
- Gemini 3.6 Flash94.1%
- Claude Opus 593.9%
- GPT-5.6 Sol93.5%
- Grok 4.593.4%
- GPT-5.6 Terra93.3%
- GPT-5.493.3%
- DeepSeek V4.1 Flash93.2%
- Grok 4.693.2%
- Kimi K393.1%
- Grok 4.792.7%
- Qwen3.8 Max92.3%
- DeepSeek V4 Pro91.7%
- GPT-5.6 Luna91.6%
- Claude Opus 4.891%
- GLM-5.390.9%
- Claude Opus 5.590.6%
- GPT-6 Luna90.5%
- GLM-5.3-Flash90.2%
- Claude Haiku 5.589.6%
- Muse Spark Open88.6%
- Claude Opus 4.688.4%
- Kimi K2.7 Code87.9%
- Claude Opus 4.786.4%
- Claude Opus 4.586%
- Claude Fable 585.9%
- Claude Sonnet 4.582.3%
- Claude Sonnet 580.3%
- Claude Sonnet 4.678.8%
- gpt-oss-120b75.8%
- Claude Haiku 4.571.2%
- Llama 4 Maverick67%
- Llama 4 Scout51.8%
- Kimi K3.1 Pro94.2%Moonshot AI's own figure
- GPT-5.593.5%Artificial Analysis's run
- Muse Spark 1.393.5%Artificial Analysis's run, GPQA Diamond
- Step 5 Preview93.5%StepFun's own figure, GPQA Diamond
- Claude Fable 5.193.4%Vals.ai's run
- GPT-5.3-Codex91.5%Artificial Analysis's run
- Qwen3.8 27B90.5%Artificial Analysis's run, GPQA Diamond
- Gemma 4 31B85.7%Artificial Analysis's run, GPQA Diamond
- Mistral Medium 3.574.8%Artificial Analysis's run, GPQA Diamond
The other models in the grid have no result on GPQA Diamond yet.
Hard reasoningHumanity's Last Exam
- Claude Opus 5.561.4%
- Claude Fable 5.159.1%
- Gemini 4 Argon57.1%
- Claude Fable 555.5%
- Claude Sonnet 5.555%
- Claude Opus 554.9%
- GPT-6 Astra54.7%
- GPT-6.1 Sol52.9%
- Kimi K3.1 Pro52.5%
- Muse Wonder50.1%
- GPT-5.6 Sol49.5%
- MiMo-V2.6-Pro49.4%
- Claude Opus 4.848.7%
- Muse Spark 1.348.7%
- MiniMax M3.1 Flash48%
- GPT-6 Sol47.9%
- Gemini 3.8 Flash47.8%
- Gemini 3.1 Pro Preview47%
- Kimi K346.9%
- Step 5 Preview46.5%
- GPT-6.1 Terra46.2%
- GPT-5.545.8%
- Claude Haiku 5.544.4%
- Muse Spark Open43.9%
- GPT-5.443.7%
- Ling 3.1 Flash43.5%
- DeepSeek V4.1 Flash43.3%
- Grok 4.743.1%
- Qwen3.8 Max43.1%
- GPT-5.6 Terra42.9%
- Grok 4.642.9%
- Grok 4.542.7%
- GPT-5.3-Codex42.5%
- Claude Opus 4.742.3%
- GLM-5.342.3%
- Claude Sonnet 541.3%
- GLM-5.241.1%
- DeepSeek V4 Pro41%
- Gemini 3.6 Flash40.8%
- Claude Opus 4.639.9%
- GLM-5.3-Flash39.9%
- GPT-5.6 Luna39.5%
- GPT-6 Luna38.5%
- MiMo-V2.6-Flash35.1%
- Kimi K2.7 Code35%
- Qwen3.8 27B33.9%
- Claude Sonnet 4.633.6%
- Claude Opus 4.530.1%
- Gemma 4 31B23.6%
- gpt-oss-120b19.6%
- Claude Sonnet 4.517.8%
- Mistral Medium 3.513.8%
- Claude Haiku 4.510.4%
- Llama 4 Maverick4.9%
- Llama 4 Scout3.8%
The other models in the grid have no result on Humanity's Last Exam yet.
Tool useAutomationBench-AA
- Gemini 4 Argon77.5%
- Kimi K3.1 Pro73.3%
- MiniMax M3.1 Flash72.5%
- Claude Sonnet 5.571.8%
- Claude Opus 5.569.5%
- GPT-6 Astra68.5%
- Muse Wonder68.1%
- Ling 3.1 Flash67.5%
- Grok 4.666.7%
- DeepSeek V4.1 Flash66.6%
- Grok 4.765.6%
- GPT-6.1 Sol64.9%
- MiMo-V2.6-Flash64.1%
- GLM-5.362.2%
- GPT-6 Sol61.6%
- GLM-5.3-Flash60.4%
- GPT-6.1 Terra60.2%
- GPT-5.6 Sol60.1%
- Gemini 3.8 Flash59.9%
- GPT-5.6 Terra59.6%
- Claude Fable 5.159.4%
- MiMo-V2.6-Pro58.6%
- Kimi K358.3%
- Grok 4.557.9%
- Muse Spark 1.357.9%
- Mistral Large 457.8%
- DeepSeek V4 Pro56.7%
- Claude Opus 556.6%
- Qwen3.8 Max56.2%
- Claude Fable 554.1%
- GPT-6 Luna53.2%
- Gemini 3.6 Flash53%
- Step 5 Preview51%
- GPT-5.6 Luna50.2%
- Muse Spark Open49.7%
- Qwen3.8 27B48.2%
- GPT-5.547.3%
- Claude Opus 4.845.6%
- Claude Sonnet 536.5%
- Claude Haiku 5.535.4%
- Gemini 3.1 Pro Preview35.4%
- GLM-5.228.4%
- Kimi K2.7 Code24.5%
- Claude Sonnet 4.620.1%
- Claude Sonnet 4.514.1%
- Mistral Medium 3.56.3%
- Gemma 4 31B4.9%
- Claude Haiku 4.53.2%
- gpt-oss-120b0.2%
- Llama 4 Scout0.2%
- Llama 4 Maverick0.2%
The other models in the grid have no result on AutomationBench-AA yet.
Computer useOSWorld 2.1
- Claude Opus 577.7%
- Muse Spark 1.369.6%
- Qwen3.8 27B84.3%Alibaba's own figure, OSWorld-Verified
- Gemini 3.6 Flash83%Google's own figure, OSWorld-Verified
- MiMo-V2.6-Pro82%Xiaomi's own figure, OSWorld-Verified
- Claude Opus 5.581.8%Anthropic's own figure
- MiMo-V2.6-Flash80.8%Xiaomi's own figure, OSWorld-Verified
- Claude Fable 5.180.7%Anthropic's own figure
- Muse Spark Open80.4%Meta's own figure, OSWorld-Verified
- Claude Sonnet 5.580.1%Anthropic's own figure
- Kimi K3.1 Pro79.6%Moonshot AI's own figure, OSWorld 2.1
- GPT-6.1 Sol78%OpenAI's own figure, OSWorld 2.1
- GPT-6 Astra75.8%Meta's run
- GPT-6.1 Terra74.2%OpenAI's own figure, OSWorld 2.1
- Muse Wonder72.6%Meta's own figure
- Claude Haiku 5.572.4%Anthropic's own figure, OSWorld 2.1
- DeepSeek V4.1 Flash69.3%Moonshot AI's run, OSWorld 2.1
- Gemini 4 Argon69.2%Google's own figure, OSWorld 2.0
- GPT-6 Sol64.4%OpenAI's own figure, OSWorld 2.0
- GPT-5.6 Sol62.7%OSWorld team's run, OSWorld 2.0
- MiniMax M3.1 Flash61.7%MiniMax's own figure, OSWorld 2.0
- GLM-5.3-Flash59.1%Z.ai's own figure, OSWorld 2.0
- Gemini 3.8 Flash59%Google's own figure, OSWorld 2.0
- Claude Sonnet 557%Anthropic's own figure
- Claude Opus 4.854.8%OSWorld team's run, OSWorld 2.0
- GPT-5.549.5%OSWorld team's run, OSWorld 2.0
- Claude Opus 4.748.9%OSWorld team's run, OSWorld 2.0
- GPT-6 Luna48.9%Anthropic's run, OSWorld 2.1
- Claude Sonnet 4.641.5%OSWorld team's run, OSWorld 2.0
The other models in the grid have no result on OSWorld 2.1 yet.
Long contextAA-LCR v1.1
- Kimi K388.7%
- Step 5 Preview88.3%
- Kimi K3.1 Pro86.3%
- MiMo-V2.6-Pro86.3%
- Claude Fable 5.185.3%
- Claude Opus 5.584.7%
- GPT-5.584.3%
- GPT-5.6 Sol84%
- GPT-5.6 Luna83.7%
- GPT-6 Sol83.7%
- GPT-6 Luna83.3%
- GPT-5.3-Codex83.3%
- GPT-6.1 Sol83%
- GPT-5.6 Terra83%
- Muse Spark 1.383%
- Claude Haiku 5.582.7%
- Claude Sonnet 5.582.7%
- GPT-6.1 Terra82.7%
- DeepSeek V4.1 Flash82.7%
- Claude Fable 582.3%
- Ling 3.1 Flash82.3%
- Claude Sonnet 582%
- GPT-5.482%
- Gemini 3.1 Pro Preview82%
- Qwen3.8 27B82%
- Gemini 3.8 Flash81.3%
- GPT-6 Astra80.7%
- Muse Wonder80.7%
- DeepSeek V4 Pro80.3%
- Grok 4.680.3%
- Qwen3.8 Max80.3%
- Claude Sonnet 4.680%
- Gemini 3.6 Flash80%
- GLM-5.3-Flash80%
- Gemini 4 Argon79.7%
- MiniMax M3.1 Flash79.7%
- GLM-5.379.7%
- Claude Opus 579.3%
- Kimi K2.7 Code79.3%
- Grok 4.579.3%
- Claude Opus 4.778.7%
- GLM-5.278.3%
- Muse Spark Open78.3%
- Claude Opus 4.678%
- Claude Opus 4.877.7%
- Claude Opus 4.577.3%
- Grok 4.776.7%
- Claude Haiku 4.574.3%
- MiMo-V2.6-Flash74.3%
- Claude Sonnet 4.572.3%
- Gemma 4 31B69.7%
- Mistral Medium 3.569.3%
- gpt-oss-120b52%
- Llama 4 Maverick50%
- Llama 4 Scout27.7%
The other models in the grid have no result on AA-LCR v1.1 yet.
MultimodalMMMU-Pro
- Claude Opus 5.587.7%
- GPT-6 Astra86.9%
- GPT-6.1 Sol86%
- Gemini 3.8 Flash85.6%
- Claude Opus 584.7%
- GPT-6.1 Terra84.7%
- Kimi K3.1 Pro83.9%
- GPT-5.6 Sol83.4%
- Gemini 3.6 Flash83.2%
- GPT-6 Sol82.9%
- Qwen3.8 Max82.8%
- Gemini 3.1 Pro Preview82.4%
- Muse Spark 1.382%
- Muse Spark Open80.9%
- GPT-5.6 Terra80.7%
- DeepSeek V4.1 Flash80.6%
- Kimi K380.5%
- Grok 4.580.4%
- GPT-5.579.9%
- GPT-6 Luna79.7%
- MiniMax M3.1 Flash79.1%
- Claude Opus 4.778.8%
- GPT-5.6 Luna78.6%
- GPT-5.3-Codex78.5%
- GPT-5.478.4%
- Claude Sonnet 577.3%
- Step 5 Preview76.4%
- Qwen3.8 27B76.3%
- Claude Opus 4.675.4%
- Claude Opus 4.574%
- Gemma 4 31B73.4%
- Claude Sonnet 4.673.3%
- MiMo-V2.6-Flash73.1%
- Claude Sonnet 4.568.7%
- Mistral Medium 3.564.9%
- Llama 4 Maverick62.1%
- Claude Haiku 4.558.6%
- Llama 4 Scout52.9%
- Claude Fable 5.186.3%Moonshot AI's run
- GLM-5.3-Flash86%Vals.ai's run, MMMU-Pro
The other models in the grid have no result on MMMU-Pro yet.
FactualityAA-Omniscience Accuracy
- Claude Fable 5.168.4%
- Claude Opus 5.565.5%
- Claude Fable 565.4%
- GPT-6.1 Sol61.8%
- GPT-6 Astra61.6%
- Claude Opus 560.9%
- Gemini 3.1 Pro Preview54.9%
- GPT-6 Sol54.5%
- Claude Sonnet 5.551.5%
- Gemini 3.8 Flash50.5%
- Claude Opus 4.748.9%
- Kimi K3.1 Pro48.9%
- Claude Opus 4.848.8%
- Gemini 4 Argon48.3%
- GPT-6.1 Terra47.6%
- Claude Opus 4.647%
- Claude Opus 4.546.6%
- DeepSeek V4 Pro45.2%
- MiniMax M3.1 Flash45.1%
- Grok 4.742.7%
- GPT-5.6 Terra42.3%
- Muse Spark Open42%
- Claude Sonnet 4.640.9%
- Claude Sonnet 540.1%
- GPT-6 Luna39.6%
- DeepSeek V4.1 Flash39.6%
- Muse Wonder38%
- Muse Spark 1.338%
- Step 5 Preview36.4%
- MiMo-V2.6-Pro34.8%
- Claude Haiku 5.534.7%
- Claude Sonnet 4.532.9%
- GLM-5.332.3%
- Qwen3.8 Max29.5%
- GLM-5.3-Flash28.2%
- MiMo-V2.6-Flash27.2%
- Ling 3.1 Flash26.5%
- Mistral Large 426%
- Mistral Medium 3.523%
- Claude Haiku 4.518%
- Qwen3.8 27B17.3%
- GPT-5.6 Sol69.7%Epoch AI's run, SimpleQA Verified
- Gemini 3.6 Flash66.2%Epoch AI's run, SimpleQA Verified
- GPT-5.563%Epoch AI's run, SimpleQA Verified
- Kimi K350.6%Epoch AI's run, SimpleQA Verified
- Grok 4.648.9%Epoch AI's run, SimpleQA Verified
- Grok 4.548.3%Epoch AI's run, SimpleQA Verified
- GPT-5.6 Luna41%Epoch AI's run, SimpleQA Verified
- Kimi K2.7 Code36.5%Epoch AI's run, SimpleQA Verified
- GLM-5.234.2%Epoch AI's run, SimpleQA Verified
- gpt-oss-120b16.8%OpenAI's own figure, SimpleQA
- Gemma 4 31B10.4%Epoch AI's run, SimpleQA Verified
The other models in the grid have no result on AA-Omniscience Accuracy yet.
Answers in fullSpeechMap
- Grok 4.593.1%
- Gemini 3.6 Flash87.2%
- Gemini 4 Argon87%
- Gemini 3.8 Flash86.1%
- Grok 4.683.6%
- Claude Opus 5.582.8%
- Gemma 4 31B82.3%
- Claude Sonnet 5.581.6%
- Claude Haiku 5.578.8%
- Claude Opus 573.7%
- Claude Fable 5.172.4%
- DeepSeek V4 Pro72%
- GLM-5.371.5%
- Mistral Medium 3.570.5%
- Claude Opus 4.770.2%
- Llama 4 Scout70.1%
- GPT-6.1 Sol69.5%
- GPT-6 Astra68.2%
- Claude Opus 4.867.4%
- MiMo-V2.6-Flash66.9%
- MiMo-V2.6-Pro66.5%
- Kimi K365.9%
- GLM-5.3-Flash65.4%
- Qwen3.8 Max65.3%
- Claude Fable 564.8%
- Grok 4.764.1%
- GPT-6 Sol64%
- GPT-6 Luna63.4%
- Claude Opus 4.659.9%
- Gemini 3.1 Pro Preview59.9%
- Step 5 Preview59.7%
- Llama 4 Maverick58.3%
- Claude Opus 4.557.5%
- Muse Wonder42.7%
- gpt-oss-120b36.3%
- Claude Sonnet 4.635.8%
- Claude Sonnet 4.531.4%
- Muse Spark 1.325.8%
- Claude Haiku 4.524.7%
The other models in the grid have no result on SpeechMap yet.
Instruction followingMultiChallenge
- GPT-6.1 Sol82%
- Gemini 4 Argon78.7%
- DeepSeek V4.1 Flash74.9%
- GPT-6.1 Terra74.2%
- Muse Spark Open74.2%
- Gemini 3.1 Pro Preview71.4%
- Claude Haiku 5.567.7%
- Claude Opus 4.559%
- Claude Sonnet 4.555.3%
- Claude Haiku 4.550.5%
- gpt-oss-120b45.3%
- Claude Opus 4.637.2%
- Qwen3.8 27B79.5%Alibaba's own figure, IFBench
- GPT-5.575.9%Artificial Analysis's run, IFBench
- Gemma 4 31B75.6%Artificial Analysis's run, IFBench
- GPT-5.3-Codex75.4%Artificial Analysis's run, IFBench
- GPT-5.473.9%Artificial Analysis's run, IFBench
- GLM-5.273.3%Artificial Analysis's run, IFBench
- GPT-5.6 Sol72.7%Artificial Analysis's run, IFBench
- GPT-5.6 Terra71.2%Artificial Analysis's run, IFBench
- Mistral Medium 3.568.8%Artificial Analysis's run, IFBench
- Claude Fable 563.5%Artificial Analysis's run, IFBench
- Kimi K2.7 Code63.1%Artificial Analysis's run, IFBench
- Claude Opus 4.862.2%Artificial Analysis's run, IFBench
- Claude Opus 4.758.6%Artificial Analysis's run, IFBench
- Claude Sonnet 4.656.6%Artificial Analysis's run, IFBench
- Llama 4 Maverick43%Artificial Analysis's run, IFBench
- Llama 4 Scout39.5%Artificial Analysis's run, IFBench
The other models in the grid have no result on MultiChallenge yet.
Every measure on record
Cost, speed, reliability, knowledge-work and domain results for Claude Opus 5.5 beyond the twelve chart axes, each with the run it comes from and its publisher. These stay separate measures; none is folded into the chart.
| Measure | Claude Opus 5.5 | Run | Source | Read |
|---|---|---|---|---|
| Specs and access | ||||
| Context windowThe most tokens one request can hold, as the maker states it. Size alone says nothing about how well the model uses a long input; the Long context axis measures that. | 1M | Anthropic's pricing page: Claude 4.6 and later models, except Claude Haiku 5.5, include the full 1M token context window | Anthropic | Oct 28, 2026 |
| Max outputThe most tokens the model writes in one response. | 128K | no Anthropic figure in the stored maker sources; OpenRouter lists 128,000 | OpenRouter | Oct 28, 2026 |
| ReadsThe kinds of input the model accepts. | Text, Images | Artificial Analysis | Oct 26, 2026 | |
| LicenceThe terms the weights or the service are offered under. | Commercial Terms of Service | Anthropic | Nov 1, 2026 | |
| Open weightsWhether the maker publishes the weights for anyone to run. | No | Artificial Analysis | Oct 26, 2026 | |
| Routes offering itOf the 19 clouds, gateways and coding products GILD tracks, how many offer the release today, preview included. | 15 of 19 | GILD route matrix | Oct 28, 2026 | |
| Cost | ||||
| Answer tokens per taskLower is better. Answer tokens per Intelligence Index task, reasoning excluded. | 35,237 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Cost per task, cache readsLower is better. The cache-read share of AA's cost per Intelligence Index task. | $2.42 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Cost per task, cache writesLower is better. The cache-write share of AA's cost per Intelligence Index task. | $1.07 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Cost per task, inputLower is better. The input-token share of AA's cost per Intelligence Index task. | $3.60 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Cost per task, outputLower is better. The answer-token share of AA's cost per Intelligence Index task. | $2.38 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Cost per task, reasoningLower is better. The reasoning-token share of AA's cost per Intelligence Index task. | $1.68 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Cost per taskLower is better. What one Intelligence Index task cost AA at list price, input, cache, output and reasoning tokens together. | $5.98 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Cost to run the indexLower is better. What the whole Intelligence Index run cost AA at list price. The runs cost from tens of dollars to about $13,000, so the axis is log from $10 to $100,000. | $8,708 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Output tokens per taskLower is better. Tokens the model wrote per Intelligence Index task, reasoning included: how verbose it is. | 119,166 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Reasoning tokens per taskLower is better. Reasoning tokens per Intelligence Index task. | 83,929 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Cached inputLower is better. The maker's list price for input read from its prompt cache, per million tokens. | $0.2 | Anthropic | Oct 30, 2026 | |
| Speed | ||||
| End-to-end time, 100K promptLower is better. Median seconds for a whole response with a 100,000-token prompt. | 534 s | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| End-to-end response timeLower is better. Seconds AA measures for a whole response on its standard prompt. | 717 s | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Time to first answer token, 100K promptLower is better. Median seconds to the first answer token with a 100,000-token prompt. | 529 s | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Time to first answer tokenLower is better. Seconds until the first answer token, after any reasoning, on AA's API runs. | 712 s | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Output speed, 100K promptMedian output tokens per second when the prompt is about 100,000 tokens long. | 99 tokens/s | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Output speedMedian output tokens per second on AA's API runs, with the 5th and 95th percentile when AA prints them. | 98 tokens/s | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Time per taskLower is better. Wall-clock seconds per Intelligence Index task. Runs take from about 15 s to about 33 min, so the axis is log from 1 s to 10,000 s. | 775 s | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Time to first token, 100K promptLower is better. Median seconds to the first chunk when the prompt is about 100,000 tokens long: long-input latency, separate from window size. | 529 s | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Time to first tokenLower is better. Median seconds to the first streamed chunk on AA's API runs, with the 5th and 95th percentile when AA prints them. Reasoning models spend this time thinking. | 712 s | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Reliability | ||||
| Hallucination rateLower is better. AA-Omniscience hallucination rate shows how often the model answers wrongly when it does not know and should decline. | 50.3% | Max effort | Artificial Analysis | Oct 28, 2026 |
| Omniscience accuracyShare of AA-Omniscience knowledge questions answered correctly. | 65.5% | Max effort | Artificial Analysis | Oct 28, 2026 |
| Omniscience indexAA-Omniscience index: correct answers minus wrong answers, declines neutral, -100 to 100. | 46.4 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| SimpleQA Verified (Epoch)Share of SimpleQA Verified factual questions answered correctly, best scorer, Epoch AI's run. A second factuality source beside AA-Omniscience. | 72.2% | Max effort | Epoch AI | Sep 22, 2026 |
| Knowledge work | ||||
| AA-BriefcaseAA-Briefcase overall Elo for long business deliverables, with AA's 95% interval. | 1,800 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| AnalystAgent (AA run)AA's AnalystAgent score for analyst workflows. | 56.3% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| APEX-Agents (maintainers)APEX-Agents pass@1 from the maintainers, as Epoch AI republishes it. | 73.5% | Max effort | Mercor (via Epoch AI) | Oct 26, 2026 |
| GDP-PDF (AA run)Share of GDP-PDF document tasks where every check passes. | 26.2% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| GDPval-AAGDPval-AA Elo: AA's run of economically valuable knowledge-work tasks, graded pairwise, with AA's interval. | 1,866 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| MLCR (AA run)AA's MLCR overall score for long, multi-document reading. | 27.8% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Vending-Bench 2Vending-Bench 2 final balance of a simulated vending business run by the model, as Epoch AI republishes it. | $9,235 | Andon Labs (via Epoch AI) | Oct 26, 2026 | |
| Capability beyond the chart | ||||
| AA-LCRAA long-context reasoning accuracy. | 84.7% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| ALE-BenchALE-Bench performance rating on long optimization contests, as Epoch AI republishes it. | 2,147 | High effort | Sakana AI (via Epoch AI) | Oct 26, 2026 |
| ARC-AGI-2ARC-AGI-2 score from the ARC Prize maintainers, as Epoch AI republishes it. | 91.7% | Max effort | ARC Prize Foundation (via Epoch AI) | Oct 26, 2026 |
| Chess puzzles (Epoch)Share of chess puzzles solved, Epoch AI's run. | 67% | Max effort | Epoch AI | Oct 13, 2026 |
| CritPt (AA run)Share of CritPt research-level physics problems solved in AA's run. | 31.7% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| CursorBenchCursorBench score from Cursor, as Epoch AI republishes it. | 57.8% | Max effort | Cursor (via Epoch AI) | Oct 26, 2026 |
| DTBenchDTBench accuracy, as Epoch AI republishes it. | 98.9% | Max effort | Redwood Research (via Epoch AI) | Oct 26, 2026 |
| Epoch Capabilities IndexEpoch Capabilities Index: Epoch AI's composite across its benchmark hub, with its confidence interval. | 169 | Claude Opus 5.5 | Epoch AI | Oct 26, 2026 |
| FrontierCode (AA run)AA's FrontierCode score: hard, unsaturated coding tasks. | 52.2% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| FrontierMath Tier 4 (Epoch)Share of FrontierMath Tier 4 research math problems solved, Epoch AI's run. | 95% | Max effort | Epoch AI | Sep 22, 2026 |
| FrontierMath Tiers 1 to 3 (Epoch)Share of FrontierMath Tiers 1 to 3 problems solved, Epoch AI's run. | 91.2% | Max effort | Epoch AI | Sep 22, 2026 |
| FrontierSWEFrontierSWE score, as Epoch AI republishes it. | 62.3% | Max effort | FrontierSWE (via Epoch AI) | Oct 26, 2026 |
| GPQA Diamond (Epoch)GPQA Diamond accuracy, best scorer, Epoch AI's run. | 90.6% | Max effort | Epoch AI | Sep 22, 2026 |
| Humanity's Last Exam (AA run)Share of Humanity's Last Exam questions answered correctly in AA's run. | 61.4% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Intelligence IndexArtificial Analysis Intelligence Index: AA's composite of its own evaluation runs, 0 to 100 points. | 57.6 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| IT-Bench SRE (AA run)AA's IT-Bench SRE score for incident and reliability agents. | 38.2% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| LMCALMCA score, 0 to 100, as Epoch AI republishes it. Its interval is printed only as a half-width, so it is not drawn. | 68.2 | Max effort | Redwood Research (via Epoch AI) | Oct 26, 2026 |
| MMMU-Pro (AA run)Multimodal understanding accuracy on MMMU-Pro in AA's run. | 87.7% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Mystery game puzzles (Epoch)Share of mystery game puzzles solved, Epoch AI's run. | 71% | Max effort | Epoch AI | Sep 29, 2026 |
| OTIS Mock AIME (Epoch)Share of OTIS Mock AIME 2024 to 2025 problems solved, Epoch AI's run. | 100% | Max effort | Epoch AI | Sep 22, 2026 |
| ProofBenchShare of ProofBench proofs graded correct, from Vals AI as Epoch AI republishes it. | 100% | Max effort | Vals AI (via Epoch AI) | Oct 26, 2026 |
| SciCode (AA run)SciCode subproblem accuracy in AA's run. | 66.9% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Terminal-Bench 4.0 (AA run)Share of Terminal-Bench 4.0 tasks solved in AA's own harness. | 59.6% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Terminal-Bench Science (AA run)Share of Terminal-Bench Science tasks solved in AA's harness. | 59.0% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| WebDev ArenaWebDev Arena score from human pairwise votes on web builds, with its 95% interval, as Epoch AI republishes it. | 1,820 | Max effort | LMArena (via Epoch AI) | Oct 26, 2026 |
| WeirdML v3, best runWeirdML v3 maximum performance across runs, as Epoch AI republishes it. | 49.8% | Extra-high effort | Håvard Tveit Ihle (via Epoch AI) | Oct 26, 2026 |
| Domains | ||||
| EconomicsArtificial Analysis capability score for economics questions, 0 to 100 points. | 65.6 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| EngineeringArtificial Analysis capability score for engineering questions, 0 to 100 points. | 60.4 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Finance and accountingArtificial Analysis capability score for finance and accounting questions, 0 to 100 points. | 60.7 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Healthcare and medicalArtificial Analysis capability score for healthcare and medical questions, 0 to 100 points. | 54.7 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| LegalArtificial Analysis capability score for legal questions, 0 to 100 points. | 63.3 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Strategy and operationsArtificial Analysis capability score for strategy and operations questions, 0 to 100 points. | 63.7 | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
| Harvey Legal Lab (AA run)AA's run of Harvey's legal task lab. | 4.2% | Claude Opus 5.5 (Max, Default Fallback) | Artificial Analysis | Oct 26, 2026 |
Routes, prices and uptime
Where Claude Opus 5.5 is offered, what each route charges, and how each endpoint is holding up.
Where it is offered
15 of 19 routes GILD tracks offer Claude Opus 5.5 today, preview included. Read Oct 28, 2026 from each route's own pages.
| Route | Status | Model ID | Limits and lifecycle | Sources |
|---|---|---|---|---|
| Amazon Bedrock | Available | anthropic.claude-opus-5-5 | in-Region only eu-west-2; us./eu./au./jp./global. profiles; Active, EOL not sooner than Sept 22, 2027; tiers: Standard only (Batch, Priority, Flex, Reserved not supported); context / output 1M / 128K; fast mode not offered | Amazon Web Services, Models at a glanceAmazon Web Services, Claude Opus 5.5Anthropic |
| Antigravity | Available | not statedpicker label Claude Opus 5.5 (thinking) ** | Antigravity: available on paid Google AI Pro, Ultra, Enterprise; Gemini CLI serves Gemini models only | |
| Claude Code | Available | claude-opus-5-5 | opus alias on Anthropic API, Bedrock, Agent Platform and Claude Platform on AWS; fast mode via /fast only on the Anthropic API or subscription usage credits | Anthropic, Model configurationAnthropic, Speed up responses with fast mode |
| Claude on Google Cloud (Anthropic managed) | Available | claude-opus-5-5 | Claude API model IDs (dated IDs use a hyphen); Opus 5.5 fast mode available here | Anthropic, Claude Opus 5.5Anthropic, Claude Models on Google Cloud (Anthropic managed)Anthropic, Fast mode |
| Claude Platform on AWS | Available | claude-opus-5-5 | Same ID as the Claude API; no fast mode on this route | Anthropic |
| Cursor | Available | not statedpicker label Claude Opus 5.5 | available (fast mode as claude-opus-5-5-fast); Premium plan or higher, API list price | Anysphere (Cursor)Cursor, Cursor Docs — Agent, Rules, MCP, Skills & CLICursor, Models & Pricing |
| Databricks | Available | system.ai.claude-opus-5-5 | Databricks' supported-models page, read Oct 30, 2026, lists model service name system.ai.claude-opus-5-5 with low, medium, high, xhigh and max effort levels; Databricks uses medium by default and reasoning cannot be disabled. | Databricks |
| The maker's own API | Available | claude-opus-5-5 | context / max output 1M / 128K; status per deprecations table; fast mode GA at US$8/US$40 (2x); not with Batch API or Priority Tier | Anthropic, Claude Opus 5.5Anthropic, Model deprecationsAnthropic, Pricing |
| GitHub Copilot | Available | not statedpicker label Claude Opus 5.5 | available (GA) | GitHub |
| GitHub Models | Retired | not applicableservice retired | service retired July 30, 2026 | GitHub, GitHub Models |
| Google Cloud Vertex / Agent Platform (Google managed) | Available | claude-opus-5-5 (GA) | retirement not sooner than Sept 22, 2027; input / output 1,000,000 / 128,000; global 2,000 QPM, 20M input TPM, 2M output TPM; fast mode not listed for the Google-managed route; it is listed for Claude Models on Google Cloud (Anthropic managed) | Google, Anthropic's Claude on Google Cloud modelsGoogle, Anthropic's Claude Opus 5.5 on Google CloudAnthropic |
| Microsoft Foundry | Available | claude-opus-5-5claude-opus-5-5-fast (fast deployment) | Hosted on Azure and on Anthropic; fast mode only on Azure-hosted deployments (separate claude-opus-5-5-fast model, Global and US Data Zone); no Message Batches API; context 1M | Anthropic, Claude in Microsoft FoundryAnthropic, Fast modeMicrosoft Learn |
| OpenCode | Available | claude-opus-5-5 | OpenCode Zen gateway, Anthropic Messages endpoint | Anomaly (OpenCode), ModelsOpenCode (Anomaly) |
| OpenRouter | Available | anthropic/claude-opus-5.5 | context / max completion 1,000,000 / 128,000; fast endpoint anthropic/fast at US$8/US$40 | OpenRouter, OpenRouter model list (API)OpenRouter, OpenRouter endpoints for anthropic/claude-opus-5.5-20260921OpenRouter, OpenRouter endpoints for anthropic/claude-opus-5.5 |
| Snowflake Cortex | Preview | claude-opus-5-5 | Public Preview | Snowflake |
| Windsurf / Devin | Available | claude-opus-5-5-highclaude-opus-5-5-high-fastclaude-opus-5-5-lowclaude-opus-5-5-low-fastclaude-opus-5-5-maxclaude-opus-5-5-max-fastclaude-opus-5-5-mediumclaude-opus-5-5-medium-fastclaude-opus-5-5-xhighclaude-opus-5-5-xhigh-fast | available (Low to Max, plus Fast variants) | Cognition (Devin, formerly Windsurf), AI ModelsCognition (Devin, formerly Windsurf), Compliance and Availability |
3 routes do not say: Codex, Gemini CLI and Grok Build.
What each of these 3 routes' pages say, with sources
| Route | Status | Model ID | Limits and lifecycle | Sources |
|---|---|---|---|---|
| Codex | Not stated | Codex model docs list OpenAI models only | ||
| Gemini CLI | Not stated | Region, tier and limits not stated on the route's pages. | ||
| Grok Build | Not stated | Grok Build pages name only grok-4.7 | xAI (SpaceXSI) |
Prices by route
The lowest standard rate is Claude API, at $4 / $20 per million input and output tokens. US dollars per million tokens, as each route lists them, one row per route and rate plan, cheapest standard rate first after the maker's own; a blended rate states its mix. OpenRouter's endpoints follow under one heading, each with its monitor's uptime over 1 day and 30 minutes and the context and output it serves.
| Route | Standard, in / out | Cache read | Other rates | Source, or uptime (1 day / 30 min) and limits |
|---|---|---|---|---|
| Claude APIMakerLowest | $4 / $20 | $0.2 | Cache write $8, 1-hour cacheCache write $5, 5-minute cacheFast mode $8 / $40, fast mode | Anthropic, Oct 26, 2026Anthropic, Oct 30, 2026 |
| Artificial Analysis price record | $4 / $20 | $0.2 | Blended $8, 3 input : 1 output, no cacheBlended $2.94, 7 cache-hit : 2 input : 1 outputCache write $5 | Artificial Analysis, Oct 26, 2026 |
| OpenRouter | $4 / $20 | $0.2 | Cache write $8, 1-hour cacheCache write $5, 5-minute cache | OpenRouter, Oct 28, 2026 |
| Through OpenRouter, 11 provider endpoints. OpenRouter, Oct 28, 2026 | ||||
| Amazon Bedrock | $4 / $20 | $0.2 | Cache write $8, 1-hour cacheCache write $5, 5-minute cache | Up 100% / 100%1M context, 128K output |
| Anthropic | $4 / $20 | $0.2 | Cache write $8, 1-hour cacheCache write $5, 5-minute cache | Up 100% / 100%1M context, 128K output |
| Azure (global) | $4 / $20 | $0.2 | Cache write $8, 1-hour cacheCache write $5, 5-minute cache | Up 100% / 100%1M context, 128K output |
| Claude Platform on AWS | $4 / $20 | $0.2 | Cache write $8, 1-hour cacheCache write $5, 5-minute cache | Up 100% / 100%1M context, 128K output |
| Google (global) | $4 / $20 | $0.2 | Cache write $8, 1-hour cacheCache write $5, 5-minute cache | Up 100% / 100%1M context, 128K output |
| Amazon Bedrock (eu-west-1) | $4.40 / $22 | $0.22 | Cache write $8.80, 1-hour cacheCache write $5.50, 5-minute cache | Up 100% / 100%1M context, 128K output |
| Amazon Bedrock (us-east-1) | $4.40 / $22 | $0.22 | Cache write $8.80, 1-hour cacheCache write $5.50, 5-minute cache | Up 100% / 100%1M context, 128K output |
| Azure (us) | $4.40 / $22 | $0.22 | Cache write $8.80, 1-hour cacheCache write $5.50, 5-minute cache | 1M context, 128K output |
| Google (europe) | $4.40 / $22 | $0.22 | Cache write $8.80, 1-hour cacheCache write $5.50, 5-minute cache | Up 100% / 100%1M context, 128K output |
| Google (us) | $4.40 / $22 | $0.22 | Cache write $8.80, 1-hour cacheCache write $5.50, 5-minute cache | Up 100%1M context, 128K output |
| Anthropic (fast, priority) | Cache read $0.4, priority tierCache write $16, priority tier, 1-hour cacheCache write $10, priority tier, 5-minute cachePriority $8 / $40, priority tier | Up 100% / 100%1M context, 128K output | ||
Uptime and speed by endpoint
Each provider endpoint as its monitor reports it: uptime over the last day and the last 30 minutes, output speed and time to first token, and the limits it serves. A blank is a figure the monitor does not publish for that endpoint.
| Endpoint | Uptime, 1 day | Uptime, 30 min | Output speed | First token | Context / max output | Source |
|---|---|---|---|---|---|---|
| Artificial Analysis: Amazon Bedrock | 99 tokens/s | 713 s | Artificial Analysis, Oct 28, 2026 | |||
| Artificial Analysis: Anthropic | 98 tokens/s | 700 s | Artificial Analysis, Oct 28, 2026 | |||
| Artificial Analysis: Google | 97 tokens/s | 677 s | Artificial Analysis, Oct 28, 2026 | |||
| Artificial Analysis: Microsoft Azure | 97 tokens/s | 694 s | Artificial Analysis, Oct 28, 2026 | |||
| Status page: Claude API (api.anthropic.com) | 99.7%, Calendar month: August 2026; component: Claude API (api.anthropic.com) | Anthropic, Oct 28, 2026 | ||||
| Status page: Claude API (api.anthropic.com) | 99.7%, Calendar month: September 2026; component: Claude API (api.anthropic.com) | Anthropic, Oct 28, 2026 | ||||
| Status page: Claude API (api.anthropic.com) | 99.8%, Calendar month: October 2026; component: Claude API (api.anthropic.com) | Anthropic, Oct 28, 2026 |
Lineup
Anthropic's 14 releases in 4 families, oldest to newest along each tier, with list price and speed. Claude Opus 5.5 is lit.
CurrentLegacyThis model
Price is the list price per 1M tokens, input / output. Speed is median output tokens per second. Bars share one scale across the lineup. Read between Oct 26, 2026 and Oct 28, 2026.
Claude Haiku
Anthropic's small, fast Claude model family for high-volume, latency-sensitive work.
2 releases
Claude Sonnet
Anthropic's balanced Claude model family.
4 releases
Claude Opus
Anthropic's high-capability Claude model family.
6 releases
- 4.5Legacy. In 4 products we coverPrice$5 / $25Speed58.8 tok/s
- 4.6Legacy. In 4 products we coverPrice$5 / $25Speed47.7 tok/s
- 4.7Legacy. In 4 products we coverPrice$5 / $25Speed54.7 tok/s
- 4.8Legacy. In 4 products we coverPrice$5 / $25Speed65.9 tok/s
- 5Legacy. In 4 products we coverPrice$5 / $25Speed53.3 tok/s
- This page5.5Current. In 9 products we coverPrice$4 / $20Speed98.4 tok/s
Claude Fable
Anthropic's Claude family for demanding reasoning and long-horizon agentic work.
2 releases
Where it fits
The layers of Agentic Software Development that Claude Opus 5.5 can power. A product supplies the rest.
Product & Engineering, Software Development
Agentic Software Development
- Primary role
- Foundation Model / Reasoning Engine
Claude Opus 5.5 can power coding, reasoning, and validation work inside an agentic software-development product. The Model does not itself provide the surrounding interface, execution environment, or system of record.
- Supporting
Work planning & task decomposition
The Model can assist with work planning & task decomposition when a Product supplies the necessary context and tools.
- Strong fit
Codebase context & intelligence
The provider documents long-context or codebase-oriented reasoning suitable for this layer. Anthropic's page
- Strong fit
Coding & implementation
The provider documents this Model for software-engineering and coding work. Anthropic's page
- Supporting
Debugging & investigation
The Model can assist with debugging & investigation when a Product supplies the necessary context and tools.
- Supporting
Testing & verification
The Model can assist with testing & verification when a Product supplies the necessary context and tools.
- Supporting
Code review & quality
The Model can assist with code review & quality when a Product supplies the necessary context and tools.
Products
We cover 9 products that offer Claude Opus 5.5 today: 8 subscriptions and 1 API.
Through a subscription
- Kiro+10 MixedAWS's spec-driven agent for the IDE, terminal, and cloud.
- OpenCode+27 PositiveOpen-source, MIT-licensed coding agent that edits code and runs commands from a terminal UI, desktop app, web client, or editor extension.
- Claude+44 PositiveAnthropic's general-purpose AI assistant for individuals and teams.
- Claude Code+75 Strong positiveAnthropic's agentic coding product for terminal and IDE workflows.
- Cursor+11 MixedAI coding agent and code editor for writing, reviewing, and shipping software, with agents in the editor, the terminal, and the cloud.
- GitHub Copilot+15 MixedGitHub's AI coding agents, IDE assistance, and pull request review.
- Google Antigravity−16 MixedGoogle's agent platform for software work: a desktop manager, a CLI, an IDE, and editor extensions.
- Perplexity−25 NegativeAI answer engine with cited web research, model choice, and an agent for longer tasks.
Through an API
Limits each vendor states
- KiroPro, Pro+, Pro Max, Power
- Credit cost 2.0x relative to Auto (1.0x baseline); 1M context; regions US, EU
- ClaudePro, Max, Team, Enterprise
- Runs Research on the web, in Claude Desktop and in Claude Mobile whichever model the chat uses, and falls back to Claude Opus 4.8 when needed. Anthropic publishes no per-model limit and does not list Opus 5.5 as a model you can pick.
- Claude CodePro, Max, Ultra, Team, Enterprise
- The default model on these plans.
- CursorPremium, Super, Ultra, Teams, Enterprise
- Not part of the included pool: on Premium and above, billed at the model's API list price from the first request, paid from prepaid credit (input $4, cache write $5, cache read $0.2, output $20 per million tokens); US data residency: Yes. Plus and Free do not include third-party models.
- GitHub CopilotCopilot Pro+, Copilot Max, Copilot Business, Copilot Enterprise
- Included on the Copilot plans listed. Copilot Free and Copilot Student get auto model selection only, so they cannot pick it.
- Google AntigravityGoogle AI Pro, Google AI Ultra, Enterprise
- Google AI Pro: non-trial subscriptions only. Not available on Free & Google AI Plus
- PerplexityMax
- In Perplexity's Search model picker on Max, not on Pro; usage limits apply, with no per-model figures published.
Plan access as each vendor's page states it: Amazon (Oct 28, 2026), Anthropic, support.claude.com (Oct 26, 2026), Anthropic, code.claude.com (Nov 2, 2026), Anysphere (Oct 28, 2026), GitHub (Oct 31, 2026), Google (Oct 26, 2026), Perplexity (Oct 26, 2026).
Comparisons
GILD comparisons that name Claude Opus 5.5, then those of the clouds and APIs that serve it.
- Amazon Bedrock vs Claude API: Buying Claude Through AWS or From AnthropicNames Claude Opus 5.5
- Amazon Bedrock vs Microsoft Foundry: Which Cloud AI Platform Fits Your Stack?Names Claude Opus 5.5
- Copilot Studio vs Gemini Enterprise: Building Workplace Agents on Microsoft or GoogleNames Claude Opus 5.5
- Gemini API vs Amazon Bedrock: One Model Family or a Model Marketplace?Names Claude Opus 5.5
- Gemini Enterprise Agent Platform vs Microsoft Foundry: Google Cloud or Azure for Models and AgentsNames Claude Opus 5.5
- Gemini Enterprise vs Microsoft 365 Copilot: Which Workplace Assistant Fits Your Company?Names Claude Opus 5.5
- Google Antigravity vs Cursor: Agent Manager or Editor-First?Names Claude Opus 5.5
- Google Antigravity vs Gemini CLI: Which Google Agent After the Code Assist Sunset?Names Claude Opus 5.5
- Claude API vs Gemini API: Which Model Platform Fits Your Workloads?Compares routes that serve Claude Opus 5.5
- Claude API vs OpenAI API: Top Scores or Lower Cost per Task?Compares routes that serve Claude Opus 5.5
- DeepSeek API vs Claude API: Price per Task or Controls and Residency?Compares routes that serve Claude Opus 5.5
- DeepSeek API vs OpenRouter: Buy DeepSeek From DeepSeek, or From Another Host?Compares routes that serve Claude Opus 5.5
- Gemini API vs Gemini Enterprise Agent Platform: Which Route to Gemini?Compares routes that serve Claude Opus 5.5
- LiteLLM vs OpenRouter: Run Your Own Gateway or Rent One?Compares routes that serve Claude Opus 5.5
- OpenRouter vs Portkey: Rent Model Access or Run a Governed Gateway?Compares routes that serve Claude Opus 5.5
- Together AI vs OpenRouter: One Open-Model Host or a Router Across HostsCompares routes that serve Claude Opus 5.5
What practitioners report
Strongest on Long context, weakest on Reliability.
Each figure is the share of accounts naming Claude Opus 5.5 that speak well of it on that axis. An axis is scored once praise and concerns are both on record from at least five accounts by three authors. An account from the maker, a company that sells or serves the model, or the maker's expert program is listed and counts toward no figure.
| Axis | Favorable | Accounts |
|---|---|---|
| Quality and reasoningWhether its answers and code are right on the author's own task: reasoning, accuracy, instruction following, and consistency. | 68% | 17 favorable, 8 not, 25 authors |
| Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track. | 46% | 6 favorable, 7 not, 13 authors |
| Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs. | 80% | 8 favorable, 2 not, 10 authors |
| Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers. | 38% | 6 favorable, 10 not, 16 authors |
| CostWhat the work costs: price per task, token use, and what caching and batch save. | 56% | 15 favorable, 12 not, 27 authors |
| SpeedResponse time, time to first token, and throughput. | 46% | 6 favorable, 7 not, 13 authors |
| ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked. | 13% | 1 favorable, 7 not, 8 authors |
Every model on these seven axes
| Axis | Claude Opus 5.5 | Claude Haiku 5.5 | Claude Sonnet 5.5 | Claude Fable 5.1 | Claude Opus 5 | Claude Sonnet 5 | Claude Fable 5 | Claude Opus 4.8 | Claude Opus 4.7 | Claude Sonnet 4.6 | Claude Opus 4.6 | Claude Opus 4.5 | Claude Haiku 4.5 | Claude Sonnet 4.5 | GPT-6.1 Terra | GPT-6.1 Sol | GPT-6 Luna | GPT-6 Astra | GPT-5.6 Sol | GPT-5.6 Terra | GPT-5.6 Luna | GPT-5.5 | GPT-5.4 | gpt-oss-120b | GPT-6 Sol | GPT-5.3-Codex | Gemini 4 Argon | Gemini 3.8 Flash | Gemma 4 31B | Gemini 3.1 Pro Preview | Gemini 3.6 Flash | DeepSeek V4.1 Flash | DeepSeek V4 Pro | Kimi K3.1 Pro | Kimi K3 | Kimi K2.7 Code | Mistral Large 4 | Mistral Medium 3.5 | Grok 4.7 | Grok 4.6 | Grok 4.5 | MiniMax M3.1 Flash | Mercury 3 | GLM-5.3-Flash | GLM-5.3 | GLM-5.2 | Muse Spark Open | Muse Wonder | Muse Spark 1.3 | Llama 4 Scout | Llama 4 Maverick | Qwen3.8 27B | Qwen3.8 Max | MiMo-V2.6-Pro | MiMo-V2.6-Flash | Ling 3.1 Flash | Step 5 Preview |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Quality and reasoning | 68%17 favorable, 8 not, 25 authors | 73%19 favorable, 7 not, 26 authors | 64%14 favorable, 8 not, 22 authors | 54%15 favorable, 13 not, 28 authors | 50%6 favorable, 6 not, 12 authors | 56%9 favorable, 7 not, 16 authors | 68%13 favorable, 6 not, 18 authors | 68%17 favorable, 8 not, 25 authors | 57%12 favorable, 9 not, 21 authors | 67%12 favorable, 6 not, 18 authors | 70%19 favorable, 8 not, 27 authors | 62%13 favorable, 8 not, 20 authors | 58%14 favorable, 10 not, 24 authors | 69%11 favorable, 5 not, 16 authors | 33%3 favorable, 6 not, 8 authors | 55%12 favorable, 10 not, 22 authors | 55%16 favorable, 13 not, 29 authors | 44%12 favorable, 15 not, 26 authors | 33%3 favorable, 6 not, 9 authors | 38%3 favorable, 5 not, 8 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | 33%4 favorable, 8 not, 12 authors | 33%2 favorable, 4 not, 6 authors | 58%22 favorable, 16 not, 38 authors | 31%10 favorable, 22 not, 32 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 63%22 favorable, 13 not, 35 authors | 56%27 favorable, 21 not, 45 authors | 80%24 favorable, 6 not, 28 authors | 56%20 favorable, 16 not, 36 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 61%25 favorable, 16 not, 40 authors | Only concerns on record0 favorable, 4 not, 4 authors | 59%20 favorable, 14 not, 32 authors | Only praise on record3 favorable, 0 not, 3 authors | 50%3 favorable, 3 not, 6 authors | 58%11 favorable, 8 not, 18 authors | 36%5 favorable, 9 not, 14 authors | 43%16 favorable, 21 not, 36 authors | 86%6 favorable, 1 not, 7 authors | 60%3 favorable, 2 not, 5 authors | 62%13 favorable, 8 not, 21 authors | 86%18 favorable, 3 not, 21 authors | 67%14 favorable, 7 not, 21 authors | 76%47 favorable, 15 not, 61 authors | 71%5 favorable, 2 not, 7 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 20%1 favorable, 4 not, 5 authors | Only praise on record2 favorable, 0 not, 2 authors | 53%8 favorable, 7 not, 15 authors | 44%8 favorable, 10 not, 17 authors | 71%24 favorable, 10 not, 34 authors | 57%4 favorable, 3 not, 7 authors | 22%2 favorable, 7 not, 9 authors | 40%4 favorable, 6 not, 10 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors |
| Tool use and structured output | 46%6 favorable, 7 not, 13 authors | 67%6 favorable, 3 not, 9 authors | 40%4 favorable, 6 not, 10 authors | 30%3 favorable, 7 not, 10 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | 70%7 favorable, 3 not, 10 authors | 57%4 favorable, 3 not, 7 authors | 50%4 favorable, 4 not, 8 authors | 50%4 favorable, 4 not, 8 authors | 29%2 favorable, 5 not, 7 authors | 33%4 favorable, 8 not, 12 authors | 70%7 favorable, 3 not, 10 authors | 43%3 favorable, 4 not, 6 authors | 50%3 favorable, 3 not, 6 authors | 40%2 favorable, 3 not, 5 authors | 40%4 favorable, 6 not, 10 authors | 33%3 favorable, 6 not, 9 authors | 62%8 favorable, 5 not, 13 authors | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author | No accounts yet | 27%4 favorable, 11 not, 15 authors | 56%5 favorable, 4 not, 9 authors | No accounts yet | 25%2 favorable, 6 not, 8 authors | 47%7 favorable, 8 not, 15 authors | 67%4 favorable, 2 not, 6 authors | 54%7 favorable, 6 not, 12 authors | Only concerns on record0 favorable, 1 not, 1 author | 59%10 favorable, 7 not, 17 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | 38%5 favorable, 8 not, 13 authors | Only concerns on record0 favorable, 5 not, 5 authors | 38%6 favorable, 10 not, 16 authors | Only praise on record2 favorable, 0 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | 67%4 favorable, 2 not, 6 authors | 80%8 favorable, 2 not, 10 authors | 33%2 favorable, 4 not, 6 authors | 57%4 favorable, 3 not, 7 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | Only concerns on record0 favorable, 4 not, 4 authors | 46%6 favorable, 7 not, 13 authors | Only praise on record1 favorable, 0 not, 1 author | Only concerns on record0 favorable, 5 not, 5 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author |
| Long context | 80%8 favorable, 2 not, 10 authors | 29%2 favorable, 5 not, 7 authors | 60%3 favorable, 2 not, 5 authors | 63%5 favorable, 3 not, 8 authors | 67%4 favorable, 2 not, 6 authors | 50%3 favorable, 3 not, 6 authors | 33%2 favorable, 4 not, 6 authors | 60%6 favorable, 4 not, 10 authors | 50%4 favorable, 4 not, 7 authors | 71%5 favorable, 2 not, 7 authors | 64%7 favorable, 4 not, 11 authors | 40%4 favorable, 6 not, 10 authors | 40%2 favorable, 3 not, 5 authors | 50%4 favorable, 4 not, 8 authors | Only concerns on record0 favorable, 1 not, 1 author | 38%3 favorable, 5 not, 8 authors | 20%1 favorable, 4 not, 5 authors | 27%3 favorable, 8 not, 11 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 25%2 favorable, 6 not, 8 authors | Only concerns on record0 favorable, 3 not, 3 authors | No accounts yet | 25%2 favorable, 6 not, 8 authors | 38%5 favorable, 8 not, 13 authors | 20%1 favorable, 4 not, 5 authors | 44%7 favorable, 9 not, 16 authors | Only praise on record1 favorable, 0 not, 1 author | 58%7 favorable, 5 not, 12 authors | No accounts yet | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | Only praise on record1 favorable, 0 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | No accounts yet | 42%5 favorable, 7 not, 12 authors | No accounts yet | No accounts yet | 40%2 favorable, 3 not, 5 authors | 60%3 favorable, 2 not, 5 authors | No accounts yet | 40%2 favorable, 3 not, 5 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 3 not, 3 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 75%6 favorable, 2 not, 8 authors | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | No accounts yet | No accounts yet |
| Developer experience | 38%6 favorable, 10 not, 16 authors | 25%2 favorable, 6 not, 8 authors | 38%5 favorable, 8 not, 13 authors | 50%7 favorable, 7 not, 14 authors | 25%3 favorable, 9 not, 12 authors | 29%2 favorable, 5 not, 7 authors | 25%3 favorable, 9 not, 12 authors | 53%10 favorable, 9 not, 19 authors | 29%4 favorable, 10 not, 14 authors | 57%4 favorable, 3 not, 7 authors | 45%5 favorable, 6 not, 11 authors | 67%8 favorable, 4 not, 12 authors | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 authors | 50%3 favorable, 3 not, 6 authors | Only concerns on record0 favorable, 2 not, 2 authors | 27%3 favorable, 8 not, 11 authors | 25%2 favorable, 6 not, 8 authors | 41%7 favorable, 10 not, 17 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | No accounts yet | No accounts yet | 14%1 favorable, 6 not, 7 authors | 25%3 favorable, 9 not, 12 authors | No accounts yet | 33%3 favorable, 6 not, 9 authors | 39%7 favorable, 11 not, 17 authors | Only concerns on record0 favorable, 7 not, 7 authors | 40%8 favorable, 12 not, 20 authors | No accounts yet | 35%8 favorable, 15 not, 23 authors | No accounts yet | 9%1 favorable, 10 not, 11 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | 13%2 favorable, 14 not, 16 authors | Only concerns on record0 favorable, 9 not, 9 authors | 25%5 favorable, 15 not, 20 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 7 not, 7 authors | 11%1 favorable, 8 not, 9 authors | Only concerns on record0 favorable, 3 not, 3 authors | 33%5 favorable, 10 not, 15 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 6 not, 6 authors | Only concerns on record0 favorable, 1 not, 1 author | 17%1 favorable, 5 not, 6 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | No accounts yet |
| Cost | 56%15 favorable, 12 not, 27 authors | 69%20 favorable, 9 not, 29 authors | 45%10 favorable, 12 not, 22 authors | 20%4 favorable, 16 not, 20 authors | 43%3 favorable, 4 not, 7 authors | 39%7 favorable, 11 not, 17 authors | 8%1 favorable, 11 not, 12 authors | 40%6 favorable, 9 not, 14 authors | 50%7 favorable, 7 not, 13 authors | 50%6 favorable, 6 not, 12 authors | 33%7 favorable, 14 not, 20 authors | 53%8 favorable, 7 not, 15 authors | 29%4 favorable, 10 not, 12 authors | 38%3 favorable, 5 not, 8 authors | 80%8 favorable, 2 not, 9 authors | 74%14 favorable, 5 not, 19 authors | 79%22 favorable, 6 not, 26 authors | 29%7 favorable, 17 not, 23 authors | 57%4 favorable, 3 not, 7 authors | Only concerns on record0 favorable, 1 not, 1 author | 50%3 favorable, 3 not, 6 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 63%5 favorable, 3 not, 8 authors | 60%3 favorable, 2 not, 5 authors | 55%12 favorable, 10 not, 21 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 35%7 favorable, 13 not, 20 authors | 58%14 favorable, 10 not, 23 authors | Only praise on record7 favorable, 0 not, 7 authors | 50%8 favorable, 8 not, 16 authors | Only concerns on record0 favorable, 1 not, 1 author | 66%25 favorable, 13 not, 37 authors | Only praise on record2 favorable, 0 not, 2 authors | 40%10 favorable, 15 not, 25 authors | 71%5 favorable, 2 not, 7 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 27%3 favorable, 8 not, 11 authors | Only concerns on record0 favorable, 8 not, 8 authors | 19%5 favorable, 21 not, 26 authors | 20%1 favorable, 4 not, 5 authors | Only praise on record4 favorable, 0 not, 4 authors | 80%12 favorable, 3 not, 15 authors | 50%6 favorable, 6 not, 12 authors | 76%16 favorable, 5 not, 21 authors | 35%8 favorable, 15 not, 23 authors | 71%5 favorable, 2 not, 7 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 9 not, 9 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 authors | Only concerns on record0 favorable, 2 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Only praise on record3 favorable, 0 not, 3 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author |
| Speed | 46%6 favorable, 7 not, 13 authors | 74%14 favorable, 5 not, 19 authors | 88%14 favorable, 2 not, 16 authors | 44%4 favorable, 5 not, 9 authors | 60%3 favorable, 2 not, 5 authors | 44%4 favorable, 5 not, 9 authors | 57%4 favorable, 3 not, 7 authors | 31%4 favorable, 9 not, 13 authors | 63%5 favorable, 3 not, 8 authors | 17%1 favorable, 5 not, 6 authors | 36%4 favorable, 7 not, 11 authors | 73%8 favorable, 3 not, 11 authors | 78%7 favorable, 2 not, 9 authors | 75%6 favorable, 2 not, 8 authors | 83%5 favorable, 1 not, 5 authors | 37%7 favorable, 12 not, 19 authors | 45%5 favorable, 6 not, 11 authors | 41%7 favorable, 10 not, 17 authors | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 80%4 favorable, 1 not, 5 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | No accounts yet | 85%23 favorable, 4 not, 27 authors | 57%4 favorable, 3 not, 7 authors | Only praise on record1 favorable, 0 not, 1 author | 45%5 favorable, 6 not, 11 authors | 61%19 favorable, 12 not, 31 authors | 53%10 favorable, 9 not, 17 authors | 35%6 favorable, 11 not, 16 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 68%21 favorable, 10 not, 30 authors | Only concerns on record0 favorable, 1 not, 1 author | 21%4 favorable, 15 not, 19 authors | Only concerns on record0 favorable, 2 not, 2 authors | No accounts yet | 21%3 favorable, 11 not, 14 authors | Only concerns on record0 favorable, 2 not, 2 authors | 29%5 favorable, 12 not, 17 authors | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | Only praise on record2 favorable, 0 not, 2 authors | 44%4 favorable, 5 not, 9 authors | 65%13 favorable, 7 not, 20 authors | 33%3 favorable, 6 not, 9 authors | 20%3 favorable, 12 not, 15 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | No accounts yet | 33%7 favorable, 14 not, 21 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author |
| Reliability | 13%1 favorable, 7 not, 8 authors | 20%1 favorable, 4 not, 5 authors | 18%2 favorable, 9 not, 11 authors | 9%1 favorable, 10 not, 11 authors | 13%1 favorable, 7 not, 8 authors | 63%5 favorable, 3 not, 7 authors | 22%2 favorable, 7 not, 9 authors | 17%2 favorable, 10 not, 12 authors | 18%2 favorable, 9 not, 11 authors | 17%1 favorable, 5 not, 6 authors | 20%3 favorable, 12 not, 15 authors | 38%6 favorable, 10 not, 16 authors | 29%2 favorable, 5 not, 7 authors | 40%4 favorable, 6 not, 10 authors | Only concerns on record0 favorable, 1 not, 1 author | 13%1 favorable, 7 not, 8 authors | Only concerns on record0 favorable, 5 not, 5 authors | 14%2 favorable, 12 not, 14 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 4 not, 4 authors | 17%1 favorable, 5 not, 6 authors | Only concerns on record0 favorable, 3 not, 3 authors | 5%1 favorable, 18 not, 19 authors | 15%3 favorable, 17 not, 20 authors | Only concerns on record0 favorable, 5 not, 5 authors | 14%3 favorable, 19 not, 22 authors | Only concerns on record0 favorable, 1 not, 1 author | 42%5 favorable, 7 not, 12 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 8%1 favorable, 12 not, 13 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 38%3 favorable, 5 not, 8 authors | Only concerns on record0 favorable, 4 not, 4 authors | 22%2 favorable, 7 not, 9 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | 60%3 favorable, 2 not, 5 authors | 33%2 favorable, 4 not, 5 authors | Only concerns on record0 favorable, 7 not, 7 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 9 not, 9 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 2 not, 2 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author |
The 86 accounts behind Claude Opus 5.5's figures
GILD searched Hacker News, GitHub, Reddit, X, Artificial Analysis, OpenRouter, Vals AI and the web for accounts that name Claude Opus 5.5.
Quality and reasoning 68%
- Favorable
the accuracy gains are significant and were able to free some flies
Replacing 10,000 Jev calls with one Opus 5.5 call. nim, co-founder of dessn, self-described, Sep 22, 2026. Claude Opus 5.5 across the dessn product, in place of Jev calls.
- Favorable
throwing Opus5.5 against it just works
Comment on: Mistral Large 4. AIblemblio, Hacker News commenter, self-described, Oct 6, 2026. Opus 5.5 across a broad range of personal experiments and projects.
- Unfavorable
opus5.5 would have broken the exchange mailboxes at least four times
Comment on: Sharing AI progress in mathematics. dada216, Hacker News commenter, self-described sysadmin and devops, Oct 7, 2026. Opus 5.5, often on ultra effort, on an imapsync wrapper for a mailbox migration.
- Favorable
Opus 5.5 rewrote an awful, legacy Drupal app from scratch in my preferred stack in four hours
Comment on: Drupal is now light-years ahead of its reputation. badlibrarian, Hacker News commenter, self-described, Oct 21, 2026. Opus 5.5 rewriting a legacy Drupal app.
- Favorable
now that vibe coding actually works
Comment on: PHP 8.2.35. IshKebab, Hacker News commenter, self-described, Oct 21, 2026. Opus 5.5 in Claude Code for a PHP to Rust rewrite.
- Unfavorable
as soon as you ask it for something more novel it is liable to drop the ball
Comment on: The compiler was supposed to end programming too. B4uler5, Hacker News commenter, self-described, Oct 21, 2026. Opus 5.5 on simple and novel coding tasks.
- Favorable
Opus 5.5 is a machine at getting correct code out once the concepts are in place
Comment on: The recently proposed o(n log n) integer multiplication algorithm [pdf]. black_knight, Hacker News commenter, self-described, Oct 22, 2026. Opus 5.5 on complex code alongside Fable 5.1.
- Unfavorable
Opus comes up with perfectly usable options, however Fable more often comes up with options that are more aligned with what I expect
Comment on: Kimi K3.1 scores 55 on Artificial Analysis, placed on the Pareto line. Incipient, Hacker News commenter, self-described, Oct 24, 2026. Opus 5.5 against Fable 5.1 on business-logic design questions.
- Unfavorable
You would be surprised at all the errors even Claude Opus 5.5 commits
Comment on: The foolishness of "natural language programming" (1978). prmph, Hacker News commenter, self-described, Oct 24, 2026. Claude Opus 5.5, reviewed edit by edit.
- Favorable
it has yet to fail finding the cause of an issue
Comment on: LLMs are making formal software verification feasible at a much larger scale. sadilek, Hacker News commenter, self-described, Oct 24, 2026. Opus 5.5 debugging with read-only prod DB, logs and traces.
- Favorable
Opus 5.5 consistently produces better results and explains itself better than Fable 5.1
Comment on: Listen and read USA nuclear forces Emergency Action Messages, heard on 11175 kHz. kccqzy, Hacker News commenter, self-described, Oct 24, 2026. Opus 5.5 against Fable 5.1 on the same tasks.
- Favorable
Opus 5.5 feels both consistently better than Fable
Comment on: Listen and read USA nuclear forces Emergency Action Messages, heard on 11175 kHz. D13Fd, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 against Fable.
- Favorable
Opus 5.5 fixed all the previous Opus 5 problems
Comment on: Listen and read USA nuclear forces Emergency Action Messages, heard on 11175 kHz. wycy, Hacker News commenter, self-described, Oct 26, 2026. Opus 5.5 after a month on GPT-6 Astra.
- Unfavorable
Claude in its current Opus 5.5 form has made some wild reaches in response to reasonable-seeming prompts
Comment on: We should be more ambitious with the software we build. majormajor, Hacker News commenter, self-described, Oct 24, 2026. Claude Opus 5.5 on a Java error-handling fix.
- Unfavorable
Opus 5.5 still sucks at a ton of things that make being a software engineer a software engineer
Comment on: The compiler was supposed to end programming too. goolz, Hacker News commenter, self-described, Oct 21, 2026. Opus 5.5 on software engineering work.
- Favorable
I feel like Opus 5.5 is the best at planning an implementation
Opus 5.5 for planning an implementation. Ali Homsi, software engineer, self-described, Oct 25, 2026. Opus 5.5 for implementation planning with Claude Code.
- Favorable
for complex large backend opus 5.5 is far ahead of sol 6.1
Opus 5.5 on complex large backends. Amit_KJ, X user, self-described, Oct 25, 2026. Opus 5.5 on doc-spec coding and large backends, against Sol 6.1.
- Unfavorable
fusion x opus 5.5 does stumble in similar ways it might for coding/product
Fusion with Opus 5.5. Michael Orcutt, former co-founder and CTO of Buildforce, self-described, Oct 25, 2026. Fusion with Opus 5.5.
- Favorable
is amongst the leading models in intelligence
Claude Opus 5.5 (max with fallback) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking, self-described, Oct 26, 2026. Claude Opus 5.5 at max effort with default fallback, on the Artificial Analysis Intelligence Index v4.3.2.
- Favorable
It ranks #2 of 27 models on the Vals Index with 70.18%
Claude Opus 5.5 Benchmarks, Cost and Capabilities | Vals AI. Vals AI, independent model evaluation, self-described, Oct 26, 2026. Claude Opus 5.5 at max compute effort across the Vals AI benchmark suite.
- Favorable
Opus 5.5 impressed us most when the work became more demanding
Claude Opus 5.5 for code review: More catches, different misses. Hendrik Krack and Gowtham Kishore Vijay, CodeRabbit, self-described, Sep 22, 2026. Claude Opus 5.5 in CodeRabbit's code review pipeline at Standard and Max effort configurations.
- Favorable
This is one of Anthropic's cleanest, most efficient models.
Claude Opus 5.5: An evaluation review and metrics benchmarks. Prasenjit Sarkar, Solutions Marketing Manager at Sonar, self-described, Sep 22, 2026. Claude Opus 5.5 High on Sonar's Java benchmark and SonarQube analysis.
- Favorable
For our team's daily product engineering, the new Opus is close enough to Fable 5.1 that Kieran is moving his work to it
Vibe Check: Opus 5.5 Is Pulling Our Codex Converts Back to Claude. Katie Parrott, staff writer at Every, Sep 22, 2026. Opus 5.5 in Claude Code and the Claude desktop app over seven days of Every team testing.
- Favorable
it likely represents a modest improvement upon Fable 5.1
Summary of METR's predeployment evaluation of Claude Opus 5.5. METR, independent AI evaluation organization, self-described, Sep 22, 2026. Claude Opus 5.5 through API access on five AI R&D tasks over 10 business days.
- Favorable
SWE-bench CLI is a notably difficult benchmark, with Opus 5.5 leading at 16.6%
SWE-bench CLI Benchmark & Leaderboard. Snorkel AI, independent leaderboard publisher, self-described, Oct 26, 2026. Claude Opus 5.5 on Snorkel's SWE-bench CLI, 200 frontier tasks.
- Favorable
Claude Opus 5.5 built me a playable platformer from one prompt in 20 minutes
Claude Opus 5.5 Review: Why It's My New Claude Code Default. Moe Lueker, personal blog, self-described, Oct 7, 2026. Claude Opus 5.5 in Claude Code at medium and max effort.
- Unfavorable
This is my biggest problem with opus 5.5. It's absolutely incredible in many ways, but it has no sense of "good enough"
Comment on: Redesigning Source Control at Anthropic. xnorswap, Hacker News commenter, self-described, Oct 16, 2026. Opus 5.5 on system design work.
- Favorable
caught errors that Fable 5.1 missed
Comment on: Claude Opus 5.5. yipinwong, Hacker News commenter, self-described, Sep 22, 2026. Opus 5.5 at medium effort against Fable 5.1 High on resume checking.
- Favorable
Benchmarks look fantastic, with occasional spots where Astra or Fable is still ahead.
Claude Opus 5.5 Should Raise Your Ambitions. Zvi Mowshowitz, writer on AI, self-described, Sep 26, 2026. Claude Opus 5.5 launch pricing, benchmarks and practitioner reactions.
Tool use and structured output 46%
- Favorable
But Opus just uses tools, a broad spectrum of it
Comment on: Mistral Large 4. AIblemblio, Hacker News commenter, self-described, Oct 6, 2026. Opus 5.5 across a broad range of personal experiments and projects.
- Unfavorable
telling it with words how to interact with my issue tracker and my repo
Comment on: Ask HN: How to get the most intelligence out of your agents?. qwerpy, Hacker News commenter, self-described, Oct 20, 2026. Opus 5.5 in an agent working with an issue tracker and repo.
- Favorable
it has access to logs and traces (Signoz in our case). With this, it has amazing debugging skills
Comment on: LLMs are making formal software verification feasible at a much larger scale. sadilek, Hacker News commenter, self-described, Oct 24, 2026. Opus 5.5 debugging with read-only prod DB, logs and traces.
- Favorable
I have been surprised how well it has worked at scale with many sub-agents
Comment on: We should be more ambitious with the software we build. XenophileJKO, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 on very large modeling and animation projects with many sub-agents.
- Unfavorable
getting Opus/Fable to properly spin up non-blocking sub-agents takes like four or five attempts
Comment on: Five Qwen3.8-27B models match Fable 5 Using GVS5H Harness. mabunday, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 and Fable 5.1 in Claude Code.
- Favorable
spinning off multiple subagents to run conformance tests which take 30-50 mins
Comment on: Five Qwen3.8-27B models match Fable 5 Using GVS5H Harness. magicalhippo, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 in Claude Code with subagents running conformance tests.
- Favorable
returns the typed response on us. Opus 5, Opus 5.5
fix(aws): restore structured output for Claude 5 on Bedrock. JonZeolla, GitHub pull request author on langchain-aws, self-described, Oct 20, 2026. Claude Opus 5.5 on Amazon Bedrock through LangChain, native structured output.
- Unfavorable
But tool calls were failing silently
Claude outage with silent tool-call failures. Stats Wire, AI engineer working with agents, self-described, Oct 25, 2026. Opus 5.5 in Claude Code during the October 25 outage.
- Unfavorable
Forced tool calls are retired. Applications can no longer require the next response to call a particular tool.
Claude Opus 5.5 for code review: More catches, different misses. Hendrik Krack and Gowtham Kishore Vijay, CodeRabbit, self-described, Sep 22, 2026. Claude Opus 5.5 in CodeRabbit's code review pipeline at Standard and Max effort configurations.
- Favorable
Opus 5.5 follows the skills and keeps moving
Vibe Check: Opus 5.5 Is Pulling Our Codex Converts Back to Claude. Katie Parrott, staff writer at Every, Sep 22, 2026. Opus 5.5 in Claude Code and the Claude desktop app over seven days of Every team testing.
- Favorable
Claude Opus 5.5 (Mini-SWE-agent) ranks first on Terminal-Bench 4.0 with 65.15%
Terminal-Bench 4.0 Leaderboard and Methodology. Vals AI, independent model evaluation, self-described, Oct 24, 2026. Claude Opus 5.5 with the Mini-SWE-agent harness on Terminal-Bench 4.0.
- Unfavorable
it will try to make tool calls using the "mainline" format, then have to retry them when they fail
Comment on: Tapo (Rust/Python library) now speaks TP-Link's TPAP protocol. bri3d, Hacker News commenter, self-described, Oct 6, 2026. Opus 5.5 with a modified Ghidra MCP server.
- Unfavorable
Claude Opus 5.5 and Claude Sonnet 5.5 reject both
anthropic provider: forced tool_choice (tool/any) breaks reflect on Claude Opus 5.5 / Sonnet 5.5 since v0.10.2. vpatel9202, GitHub issue author on vectorize-io/hindsight, self-described, Oct 19, 2026. claude-opus-5-5 through the Anthropic provider in Hindsight reflect.
- Unfavorable
Opus 5.5 sometimes answers Sashiko's prompt-described tools in Claude's native tool-call format instead of the
claude-cli: with
--tools "", Opus 5.5 writes tool calls as text and runs until the 10 minute timeout. someonewithpc, GitHub issue author on sashiko-dev/sashiko, self-described, Oct 24, 2026. claude-opus-5-5 at default medium effort through Claude Code 2.1.308 with no tools loaded.
Long context 80%
- Favorable
Try a bigger code base or more complex stuff and you will easily see that the solution
Comment on: Mistral Large 4. AIblemblio, Hacker News commenter, self-described, Oct 6, 2026. Opus 5.5 on bigger code bases and more complex work.
- Favorable
I've been doing PCB layout with Opus 5.5. Maybe this was possible easlier and with Chinese models, but I feel this really pushes the model. These are 10hr jobs
Comment on: DeepInfer: High-performance inference framework for DeepSeek models. edg5000, Hacker News commenter, self-described, Oct 21, 2026. Opus 5.5 on 10-hour PCB layout jobs.
- Favorable
Certainly in the older models they hit a complexity limit, but I haven't really hit it with Opus 5.5
Comment on: We should be more ambitious with the software we build. XenophileJKO, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 on very large modeling and animation projects with many sub-agents.
- Unfavorable
the speed goes down very fast once you reach a certain level of complexity
Comment on: We should be more ambitious with the software we build. toonvanvr, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 on long-standing complex projects.
- Favorable
also excellent memory management on the project
Opus 5.5 on complex large backends. Amit_KJ, X user, self-described, Oct 25, 2026. Opus 5.5 on doc-spec coding and large backends, against Sol 6.1.
- Unfavorable
keep each task under ~100k tokens of context, quality drops past that
100+ hours running Opus 5.5 inside Claude Code. Layton Gott, X user, self-described, Oct 25, 2026. Opus 5.5 inside Claude Code, including overnight loops, over 100+ hours.
- Favorable
our hands-on coding experiments produced substantial results on tasks that ran for hours
Claude Opus 5.5 for code review: More catches, different misses. Hendrik Krack and Gowtham Kishore Vijay, CodeRabbit, self-described, Sep 22, 2026. Claude Opus 5.5 in CodeRabbit's code review pipeline at Standard and Max effort configurations.
- Unfavorable
Claude Opus 5.5 still has qualitative weaknesses that an expert human is unlikely to exhibit when solving hard, long-horizon tasks
Summary of METR's predeployment evaluation of Claude Opus 5.5. METR, independent AI evaluation organization, self-described, Sep 22, 2026. Claude Opus 5.5 through API access on five AI R&D tasks over 10 business days.
- Favorable
I barely compact at work in a very complex monorepo (neither with Fable 5.1 nor Opus 5.5)
Comment on: GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price. kaoD, Hacker News commenter, self-described, Sep 30, 2026. Opus 5.5 and Fable 5.1 in a very complex work monorepo.
- Favorable
Opus 5.5 seems like the real deal again, consistent good results on large, complex codebases
Comment on: GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price. btbuildem, Hacker News commenter, self-described, Sep 29, 2026. Opus 5.5 on large, complex codebases.
- Favorable
It holds every issue in mind at once and connects them in ways I never did
Comment on: How to engineer an AI harness for game development. BatFastard, Hacker News commenter, self-described, Oct 14, 2026. Opus 5.5 run overnight on game engine issues.
Developer experience 38%
- Favorable
I tell it a simple narrative and it follows through
Comment on: Gemini 4 Argon. ramoz, Hacker News commenter, self-described, Oct 13, 2026. Opus 5.5 driving screen recordings from a short narrative.
- Unfavorable
Mostly because of its overly restrictive auto-mode guardrails and brittle command whitelisting
Comment on: Ask HN: How to get the most intelligence out of your agents?. qwerpy, Hacker News commenter, self-described, Oct 20, 2026. Opus 5.5 in an agent working with an issue tracker and repo.
- Unfavorable
Opus 5.5 speak is still cause aneurysms for my brain
Comment on: DeepInfer: High-performance inference framework for DeepSeek models. GreenWatermelon, Hacker News commenter, self-described, Oct 20, 2026. Opus 5.5 tried now and then alongside a DeepSeek 4.1 Flash daily driver.
- Unfavorable
I still find it wildly unacceptable for models that are so good at writing software
Comment on: Every AI model has the same "controversial" take on humans. km144, Hacker News commenter, self-described, Oct 23, 2026. Opus 5.5 prose output.
- Unfavorable
Opus 5.5 can fix everything but the guardrails trigger too easily
Comment on: Kimi K3.1 Pro and K3.1 Pro Highspeed. arjie, Hacker News commenter, self-described, Oct 23, 2026. Opus 5.5 on defensive security work on the commenter's own software.
- Unfavorable
I rarely use it because it refuses to do anything cyber-related
Comment on: Kimi K3.1 Pro and K3.1 Pro Highspeed. DaSHacka, Hacker News commenter, self-described, Oct 23, 2026. Opus 5.5 on a Claude subscription.
- Favorable
Even I was surprised by how well it all works now out of the box
Comment on: No signs of AI payoff outside the tech sector. kolinko, Hacker News commenter, self-described, Oct 24, 2026. Opus 5.5 in Claude Code for nontechnical colleagues.
- Favorable
Opus 5.5 writes concisely and
Comment on: Listen and read USA nuclear forces Emergency Action Messages, heard on 11175 kHz. rafram, Hacker News commenter, self-described, Oct 24, 2026. Opus 5.5 writing style against Fable.
- Favorable
You can prompt Opus 5.5 into writing well.
Comment on: Listen and read USA nuclear forces Emergency Action Messages, heard on 11175 kHz. KerrAvon, Hacker News commenter, self-described, Oct 24, 2026. Opus 5.5 prompted for prose.
- Unfavorable
the default style of Opus 5.5 is still terrible but it is way better than 5.0
Comment on: Listen and read USA nuclear forces Emergency Action Messages, heard on 11175 kHz. temac, Hacker News commenter, self-described, Oct 24, 2026. Opus 5.5 default writing style against Opus 5.
- Unfavorable
Claude (Opus 5.5 in this case) tends to just go off and do things
A week of Claude Code after Codex. Michael Struwig, X user, self-described, Oct 23, 2026. Opus 5.5 in Claude Code after a long time on Codex.
- Favorable
5.5's effort settings also scale the way Kieran expects
Vibe Check: Opus 5.5 Is Pulling Our Codex Converts Back to Claude. Katie Parrott, staff writer at Every, Sep 22, 2026. Opus 5.5 in Claude Code and the Claude desktop app over seven days of Every team testing.
- Unfavorable
Foundry still offers no EU data zone, batch pricing or fast mode
Claude Opus 5.5 in Foundry: the Opus 5 migration cost math. Falak Mahmood, CEO and co-founder of Technspire, Sep 24, 2026. Claude Opus 5.5 in Microsoft Foundry for a 60-turn cache-heavy agent session.
Anthropic's pricing page now lists fast mode for Claude Opus 5.5 on Claude in Microsoft Foundry for deployments hosted on Azure, at $8 per million input tokens and $40 per million output tokens. Anthropic's page
- Unfavorable
Opus 5.5's safeguards flagged this session
Comment on: Prompting Claude Opus 5.5. idiocrat, Hacker News commenter, self-described, Sep 28, 2026. Opus 5.5 reviewing the commenter's own authentication code.
- Favorable
5.5 communicates like a real collaborator and not something that constantly demands my mental energy to decode
Comment on: Claude Opus 5.5. desmondl, Hacker News commenter, self-described, Sep 23, 2026. Opus 5.5 on a live sports scheduling application.
- Unfavorable
What bothers me most with Opus 5.5 is its verbosity
Comment on: Prompting Claude Opus 5.5. user43928, Hacker News commenter, self-described, Sep 28, 2026. Opus 5.5 in Claude Code with the Concise output style.
Cost 56%
- Unfavorable
Overall, it's a bit more expensive
Replacing 10,000 Jev calls with one Opus 5.5 call. nim, co-founder of dessn, self-described, Sep 22, 2026. Claude Opus 5.5 across the dessn product, in place of Jev calls.
- Favorable
price drop is good so I can stop juggling different models
Comment on: Claude Opus 5.5. coffeebeqn, Hacker News commenter, self-described, Sep 22, 2026. Opus 5.5 at its new price, for daily team use.
- Unfavorable
a flagship model like Opus 5.5, which charges 100x more
Comment on: DeepInfer: High-performance inference framework for DeepSeek models. pu_pe, Hacker News commenter, self-described, Oct 20, 2026. Opus 5.5 API pricing against DeepSeek 4 Flash.
- Unfavorable
that would be ~150 bucks on Opus 5.5
Comment on: DeepSeek just open-sourced its inference engine. mobelkh, Hacker News commenter, self-described, Oct 20, 2026. Opus 5.5 API pricing for a 550M-token workload.
- Unfavorable
At least if you have $1k or so to burn on Opus 5.5
Comment on: PHP 8.2.35. IshKebab, Hacker News commenter, self-described, Oct 21, 2026. Opus 5.5 in Claude Code for a PHP to Rust rewrite.
- Unfavorable
Opus 5.5 is even more verbose. 260M on the same suite.
Comment on: Kimi K3.1 Pro and K3.1 Pro Highspeed. ctolsen, Hacker News commenter, self-described, Oct 23, 2026. Opus 5.5 token output on the Artificial Analysis Intelligence Index suite.
- Favorable
Opus 5.5 high trails K3.1 by 1 point, but outputs only 53M tokens, so it indeed comes out cheaper per-task
Comment on: Kimi K3.1 Pro and K3.1 Pro Highspeed. thepasch, Hacker News commenter, self-described, Oct 23, 2026. Opus 5.5 at high, xhigh and max effort on the Artificial Analysis index.
- Favorable
particularly how cheap it is in practice
Comment on: Kimi K3.1 scores 55 on Artificial Analysis, placed on the Pareto line. mwigdahl, Hacker News commenter, self-described, Oct 23, 2026. Opus 5.5 in Claude Code on a subscription.
- Favorable
Opus 5.5 consumes a lot less usage than 5.0 did, so it goes further
Comment on: Kimi K3.1 Pro and K3.1 Pro Highspeed. Wowfunhappy, Hacker News commenter, self-described, Oct 23, 2026. Opus 5.5 usage on a Claude subscription.
- Favorable
I used Opus 5.5 on a $20 plan
Comment on: We should be more ambitious with the software we build. codazoda, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 on a $20 plan finishing a BASIC interpreter.
- Favorable
Opus 5.5 is so good and so token efficient
Comment on: Listen and read USA nuclear forces Emergency Action Messages, heard on 11175 kHz. wycy, Hacker News commenter, self-described, Oct 26, 2026. Opus 5.5 after a month on GPT-6 Astra.
- Favorable
With Opus 5.5 on medium and high I'm not anywhere close to hitting limits on my 20x sub
Comment on: OpenAI and Anthropic cut their LLM prices by up to 80% within a few months. Why?. weird-eye-issue, Hacker News commenter, self-described, Oct 26, 2026. Opus 5.5 at medium and high effort on a 20x subscription.
- Unfavorable
it takes Opus 5.5 over $1000 in API spend to return an answer correctly on
Comment on: IBM CEO says open weight models are now good and cheap on-prem. hhh, Hacker News commenter, self-described, Oct 26, 2026. Opus 5.5 through the API on a legacy codebase.
- Unfavorable
even though it's expensive
Opus 5.5 for planning an implementation. Ali Homsi, software engineer, self-described, Oct 25, 2026. Opus 5.5 for implementation planning with Claude Code.
- Unfavorable
Kimi did it for 1/5 of the Claude price
Same Three.js carousel prompt on Opus 5.5, ChatGPT and Kimi K3.1 Pro. HavisT83099, X user, self-described, Oct 25, 2026. Claude Opus 5.5 on one Three.js prompt against ChatGPT and Kimi K3.1 Pro.
- Unfavorable
one of my sessions hit 98% cache and still cost $200 API-equivalent in 30 minutes
100+ hours running Opus 5.5 inside Claude Code. Layton Gott, X user, self-described, Oct 25, 2026. Opus 5.5 inside Claude Code, including overnight loops, over 100+ hours.
- Unfavorable
Claude Opus 5.5 vs Sonnet 5.5 on one prompt: $7.60 vs $4.65 at est. API list price
Claude Opus 5.5 vs Sonnet 5.5 on one prompt. Jeff Bruchado, software engineer building products with AI, self-described, Oct 25, 2026. Claude Opus 5.5 at high effort with Read, Write and Edit tools, against Sonnet 5.5.
- Unfavorable
The cost is not close, so Deepseek won based on cost
Opus 5.5 with subagents. Noah, software engineer and LSP author, self-described, Oct 24, 2026. Opus 5.5 working with subagents, against Sonnet 5.5 and DeepSeek v4.1.
- Unfavorable
but somewhat expensive when comparing to other models of similar price
Claude Opus 5.5 (max with fallback) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking, self-described, Oct 26, 2026. Claude Opus 5.5 at max effort with default fallback, on the Artificial Analysis Intelligence Index v4.3.2.
- Unfavorable
Our evaluation team reported higher token usage than the production model mix in every tested configuration
Claude Opus 5.5 for code review: More catches, different misses. Hendrik Krack and Gowtham Kishore Vijay, CodeRabbit, self-described, Sep 22, 2026. Claude Opus 5.5 in CodeRabbit's code review pipeline at Standard and Max effort configurations.
- Favorable
and uses 40% fewer tokens to do it
Claude Opus 5.5: An evaluation review and metrics benchmarks. Prasenjit Sarkar, Solutions Marketing Manager at Sonar, self-described, Sep 22, 2026. Claude Opus 5.5 High on Sonar's Java benchmark and SonarQube analysis.
- Favorable
Fable-level power at roughly 60 percent less than Fable's token price makes Opus 5.5 impossible to ignore
Vibe Check: Opus 5.5 Is Pulling Our Codex Converts Back to Claude. Katie Parrott, staff writer at Every, Sep 22, 2026. Opus 5.5 in Claude Code and the Claude desktop app over seven days of Every team testing.
- Favorable
found that medium effort matches max at 1/7 the cost
Claude Opus 5.5 Review: Why It's My New Claude Code Default. Moe Lueker, personal blog, self-described, Oct 7, 2026. Claude Opus 5.5 in Claude Code at medium and max effort.
- Favorable
which cuts a cache-heavy 60-turn agent session from $8.63 on Opus 5 to $5.10
Claude Opus 5.5 in Foundry: the Opus 5 migration cost math. Falak Mahmood, CEO and co-founder of Technspire, Sep 24, 2026. Claude Opus 5.5 in Microsoft Foundry for a 60-turn cache-heavy agent session.
- Favorable
it's about 10x the usage of Fable 5.1 with similar, perhaps greater levels of intelligence
Comment on: Claude partial outage. jjordan, Hacker News commenter, self-described, Sep 29, 2026. Opus 5.5 on a Claude subscription in the week after release.
- Favorable
Opus 5.5 (med, as it's better than F5.1 high per graph in the article) used $2.2
Comment on: Claude Opus 5.5. yipinwong, Hacker News commenter, self-described, Sep 22, 2026. Opus 5.5 at medium effort against Fable 5.1 High on resume checking.
- Favorable
This is all a very good price for Fable or Astra level performance.
Claude Opus 5.5 Should Raise Your Ambitions. Zvi Mowshowitz, writer on AI, self-described, Sep 26, 2026. Claude Opus 5.5 launch pricing, benchmarks and practitioner reactions.
- Favorable
Opus 5.5 appears to define essentially the entire cost/performance frontier
Comment on: Claude Opus 5.5. Gareth321, Hacker News commenter, self-described, Sep 23, 2026. Opus 5.5 effort levels on the Artificial Analysis cost per task table.
Speed 46%
- Unfavorable
Opus 5.5 takes 30.0 and GPT-6 Astra 16.7
Sonnet 5.5 at medium effort for chat apps. Gabriele Bolognese, backend developer and founder of FlashFX, self-described, Oct 2, 2026. Opus 5.5 through the Claude API for a chat app, against Sonnet 5.5 at medium and GPT-6 Astra.
- Unfavorable
a bit more expensive and slightly slower
Replacing 10,000 Jev calls with one Opus 5.5 call. nim, co-founder of dessn, self-described, Sep 22, 2026. Claude Opus 5.5 across the dessn product, in place of Jev calls.
- Unfavorable
And it felt much slower to boot
Comment on: Kimi K3.1 Pro and K3.1 Pro Highspeed. LeFantome, Hacker News commenter, self-described, Oct 23, 2026. Opus 5.5 on a $30 a month Claude subscription.
- Favorable
Opus 5.5 feels both consistently better than Fable and faster.
Comment on: Listen and read USA nuclear forces Emergency Action Messages, heard on 11175 kHz. D13Fd, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 against Fable.
- Favorable
the tps of 6.1 sol ultrafast is usually lower than opus 5.5 fast
Comment on: Cerebras Deploys Trillion-Parameter AI Models. chrismustcode, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 fast mode on OpenRouter.
- Unfavorable
It is not good at it! And very slow!
Comment on: fheroes2: A recreation of Heroes of Might and Magic II game engine. skolos, Hacker News commenter, self-described, Oct 25, 2026. Claude Code with Opus 5.5 playing HOMM3 through an MCP server.
- Unfavorable
Opus 5.5 is smart enough now, speed is what we need
Comment on: Cerebras Deploys Trillion-Parameter AI Models. amelius, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 in coding agents.
- Favorable
Claude Opus 5.5: 13 min, ~$2.12
Same Three.js carousel prompt on Opus 5.5, ChatGPT and Kimi K3.1 Pro. HavisT83099, X user, self-described, Oct 25, 2026. Claude Opus 5.5 on one Three.js prompt against ChatGPT and Kimi K3.1 Pro.
- Favorable
What I found most surprising about working with subagents: Opus 5.5 is really fast
Opus 5.5 with subagents. Noah, software engineer and LSP author, self-described, Oct 24, 2026. Opus 5.5 working with subagents, against Sonnet 5.5 and DeepSeek v4.1.
- Favorable
It's also faster than average
Claude Opus 5.5 (max with fallback) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking, self-described, Oct 26, 2026. Claude Opus 5.5 at max effort with default fallback, on the Artificial Analysis Intelligence Index v4.3.2.
- Unfavorable
although it took longer to build than our Fable example
Claude Opus 5.5 for code review: More catches, different misses. Hendrik Krack and Gowtham Kishore Vijay, CodeRabbit, self-described, Sep 22, 2026. Claude Opus 5.5 in CodeRabbit's code review pipeline at Standard and Max effort configurations.
- Favorable
even something like Opus 5.5 on fast reliably hits 330tps+
Comment on: Mistral Large 4. Topfi, Hacker News commenter, self-described, Oct 7, 2026. Opus 5.5 in fast mode.
- Favorable
It's always faster than I would have been
Comment on: How to engineer an AI harness for game development. BatFastard, Hacker News commenter, self-described, Oct 14, 2026. Opus 5.5 run overnight on game engine issues.
- Unfavorable
Claude Opus 5.5 is still slower than GPT-5.6 Sol on the tool and intermediate-tool latency suites
perf: find where Claude Opus 5.5 spends tool-loop time using the [ToolRound] logs. onoya, GitHub issue author on Bike4Mind/bike4mind, self-described, Oct 21, 2026. Claude Opus 5.5 on Bike4Mind's tool and intermediate-tool latency suites.
Reliability 13%
- Unfavorable
opus-5.5 has been declining a lot lately
Comment on: GameFrame: Agentic Framework for Reverse Engineering Games. matt3210, Hacker News commenter, self-described, Oct 22, 2026. Opus 5.5 as a coding agent against GPT-6 Astra.
- Unfavorable
After about 30 minutes I hit a 5 hour limit
Comment on: Kimi K3.1 Pro and K3.1 Pro Highspeed. LeFantome, Hacker News commenter, self-described, Oct 23, 2026. Opus 5.5 on a $30 a month Claude subscription.
- Unfavorable
make it more than 4 hours on Opus 5.5 without getting my session paused for the day
Comment on: Ask HN: Find Vulns with Claude in OSS?. Bender, Hacker News commenter, self-described, Oct 24, 2026. Opus 5.5 on defensive security coding.
- Unfavorable
I experienced a regression some days ago, where Claude Code with Opus 5.5
Comment on: Five Qwen3.8-27B models match Fable 5 Using GVS5H Harness. magicalhippo, Hacker News commenter, self-described, Oct 25, 2026. Opus 5.5 in Claude Code with subagents running conformance tests.
- Unfavorable
Affected models: Claude Mythos 5.1, Fable 5.1, Opus 5.5, Sonnet 5.5 and Haiku 5.5
Anthropic elevated errors for multiple models. atnomos, X user, self-described, Oct 25, 2026. Opus 5.5 in Claude Code and the Claude API during the October 25 incident.
- Unfavorable
Claude had a real outage today across Opus 5.5, Sonnet 5.5, Fable 5.1 and Mythos 5.1
Claude outage with silent tool-call failures. Stats Wire, AI engineer working with agents, self-described, Oct 25, 2026. Opus 5.5 in Claude Code during the October 25 outage.
- Favorable
Uptime (3d) The model was reachable. Request routed to a provider. 100.00%
Claude Opus 5.5 - API Pricing & Benchmarks | OpenRouter. OpenRouter, model routing platform publishing provider uptime, self-described, Oct 26, 2026. Claude Opus 5.5 across its OpenRouter providers over the past 3 days.
- Unfavorable
Kieran and Nityesh hit their weekly limits during testing
Vibe Check: Opus 5.5 Is Pulling Our Codex Converts Back to Claude. Katie Parrott, staff writer at Every, Sep 22, 2026. Opus 5.5 in Claude Code and the Claude desktop app over seven days of Every team testing.
- Favorable
I'm surprised it took this long since release for their first outage
Comment on: Claude partial outage. jjordan, Hacker News commenter, self-described, Sep 29, 2026. Opus 5.5 on a Claude subscription in the week after release.
Alternatives
Current models we would weigh against Claude Opus 5.5, and the reason for each.
- GPT Astra family by OpenAIGPT-6 AstraA direct frontier alternative for complex end-to-end professional and engineering work.Open the model
- Gemini Pro family by GoogleGemini 3.1 Pro PreviewAn advanced reasoning and multimodal alternative for complex work across varied inputs.Open the model
- Claude Sonnet family by AnthropicClaude Sonnet 5.5A same-provider alternative when speed and everyday efficiency matter more than maximum capability.Open the model
