Speed
52tokens a second
Output speed. How fast it writes once the answer starts. Run at max effort.
- First token
- 25 s
- Whole answer
- 35 s
Claude Opus model by Anthropic
Claude Opus 4.7
An earlier Claude Opus release, still available on the Claude API.
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.You are on Claude Opus 4.7. Current:Claude Opus 5.5
- Claude FableAnthropic's Claude family for demanding reasoning and long-horizon agentic work.Claude Fable 5.1
Strengths and weaknesses
Compare with other models Up to 3 beside Claude Opus 4.7
- Claude Opus 4.7
Suggested comparisons
The models a buyer weighs against Claude Opus 4.7, picked on list price and on Artificial Analysis's Intelligence Index of overall quality. Add one to draw it beside Claude Opus 4.7.
Claude Opus 4.7
Ranked against the 40 current releases on this chart, Claude Opus 4.7 ranks 8th of 31 on Factuality. On Computer use, OSWorld team's runs on OSWorld 2.0 put Claude Opus 4.7 5.9 points under Claude Opus 4.8 and 7.4 points above Claude Sonnet 4.6. Instruction following is Artificial Analysis's run on IFBench, marked on the chart. It ranks lowest on Science, 24th of 25 and Long context, 32nd of 39. Agentic coding and Tool use: 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 4.7This pageResults on 10 of 12 axes$5 / $2555 tokens/sFirst token in 22 s
Prices and speeds read between Oct 26, 2026 and Oct 28, 2026.
Claude Opus 4.7 on each axis10 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 4.7Not yet published by Anthropic or any independent evaluator, checked Nov 2, 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 4.754.5%
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 4.770.2%
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 4.786.4%
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 4.742.3%
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 4.7Not yet published by Anthropic or any independent evaluator, checked Nov 2, 2026
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. Where it has no run of a model, the maker's own figure or another lab's run stands in, marked with its benchmark.
- Claude Opus 4.748.9%OSWorld team's runBenchmark: OSWorld 2.0, partial score, full task set, v2026.06.24 release. From another source, so it is drawn and marked but not ranked with the others.The OSWorld team's own run at max effort with its batched tool and a 500-step budget, on the v2026.08.08 task release. It fully completed 18.2% of tasks; the standard tool setting scored 49.1.
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 4.778.7%
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 4.778.8%
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 4.748.9%Hallucination rate 42.3% 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 4.770.2%With reasoning on, SpeechMap counted 22.0% of requests denied and 5.1% evaded. With reasoning off, the model completes 71.5%.2.7% 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. Where it has no run of a model, the maker's own figure or another lab's run stands in, marked with its benchmark.
- Claude Opus 4.758.6%Artificial Analysis's runBenchmark: IFBench, accuracy, Artificial Analysis IFBench run. From another source, so it is drawn and marked but not ranked with the others.Artificial Analysis ran Claude Opus 4.7 at max effort in its own evaluation harness.
Cost, speed, capacity, quality and accuracy for Claude Opus 4.7, with where each figure sits among the 41 models GILD tracks. These measures stand beside the chart and never feed it.
Capacity
1Mtokens
Context window. The most one request can hold, as the maker states it.
- Reads
- Text, Images
Quality
40.7of 100
Intelligence Index. One composite score across independent evaluations. Run at max effort.
- GDPval knowledge work
- 1,353 Elo
- Epoch Capabilities Index
- 157
Hallucination
42.3%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
- 48.9%
Where you can get it
13of 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, Epoch AI and GILD's route matrix, read Oct 26 to Nov 1, 2026. Each measure's definition and source open under . Not yet published for Claude Opus 4.7: Cost per task, Cached input, Max output and Terminal-Bench 4.0.
Every value with its benchmark, run and source
| Axis | Benchmark and setting | Claude Opus 4.7 | Run | Source | Date |
|---|---|---|---|---|---|
| Agentic coding | Terminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness | Not yet published by Anthropic or any independent evaluator, checked Nov 2, 2026 | |||
| Code | SciCodeSubproblem accuracy, pass@1, highest effort run | 54.5% | Effort: max. Harness: none. | Artificial Analysis (via Epoch AI) | Apr 16, 2026 |
| Math | FrontierMath Tiers 1-3Accuracy, pass@1, highest effort run | 70.2% | Effort: max. Harness: none. | Epoch AI | Apr 16, 2026 |
| Science | GPQA DiamondAccuracy, pass@1, highest effort run | 86.4% | Effort: max. Harness: none. | Epoch AI | Apr 16, 2026 |
| Hard reasoning | Humanity's Last ExamAccuracy, text-only questions, no tools | 42.3% | Claude Opus 4.7 (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Tool use | AutomationBench-AAScore, Artificial Analysis run | Not yet published by Anthropic or any independent evaluator, checked Nov 2, 2026 | |||
| Computer use | OSWorld 2.0Partial score, full task set, v2026.06.24 release. The OSWorld team's own run at max effort with its batched tool and a 500-step budget, on the v2026.08.08 task release. It fully completed 18.2% of tasks; the standard tool setting scored 49.1.Stands in for OSWorld 2.1, partial score, full 108-task set, v2.1 release, which has no run of Claude Opus 4.7 yet. | 48.9% | Claude Opus 4.7Effort: max. Harness: OSWorld team harness. | OSWorld teamRun by OSWorld team | Oct 15, 2026 |
| Long context | AA-LCR v1.1Accuracy, Artificial Analysis run | 78.7% | Claude Opus 4.7 (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Multimodal | MMMU-ProOverall accuracy, no tools | 78.8% | Claude Opus 4.7 (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Factuality | AA-Omniscience AccuracyAccuracy, Artificial Analysis run | 48.9%Hallucination rate 42.3% in the same run (lower is better) | Claude Opus 4.7 (Max)Effort: max. Harness: none. | Artificial Analysis | Oct 26, 2026 |
| Answers in full | SpeechMap% Complete over 2,120 contested requests, reasoning-on entry. With reasoning on, SpeechMap counted 22.0% of requests denied and 5.1% evaded. With reasoning off, the model completes 71.5%. | 70.2%2.7% of requests failed at the provider and count against it | Effort: reasoning on. Harness: none. | SpeechMap.AI | Oct 27, 2026 |
| Instruction following | IFBenchAccuracy, Artificial Analysis IFBench run. Artificial Analysis ran Claude Opus 4.7 at max effort in its own evaluation harness.Stands in for MultiChallenge, accuracy, Scale AI run, which has no run of Claude Opus 4.7 yet. | 58.6% | Claude Opus 4.7 (Max)Effort: max. Harness: none. | Artificial AnalysisRun by Artificial Analysis | Oct 28, 2026 |
Price and speed
- Claude Opus 4.7 lists at $5 per million input tokens and $25 per million output tokens. Anthropic pricing, Oct 26, 2026.
- Claude Opus 4.7, at max effort, writes 54.7 output tokens per second on Anthropic's API, and its first token arrives 22 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 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 4.7 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 4.7 | 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 |
| 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. | 13 of 19 | GILD route matrix | Oct 28, 2026 | |
| Speed | ||||
| End-to-end response timeLower is better. Seconds AA measures for a whole response on its standard prompt. | 35 s | Claude Opus 4.7 (Max) | 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. | 25 s | Claude Opus 4.7 (Max) | 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. | 52 tokens/s | Claude Opus 4.7 (Max) | 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. | 25 s | Claude Opus 4.7 (Max) | 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. | 42.3% | Max effort | Artificial Analysis | Oct 26, 2026 |
| Omniscience accuracyShare of AA-Omniscience knowledge questions answered correctly. | 48.9% | Max effort | Artificial Analysis | Oct 26, 2026 |
| Omniscience indexAA-Omniscience index: correct answers minus wrong answers, declines neutral, -100 to 100. | 27.3 | Claude Opus 4.7 (Max) | 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. | 51.7% | Extra-high effort | Epoch AI | Aug 27, 2026 |
| Knowledge work | ||||
| AA-BriefcaseAA-Briefcase overall Elo for long business deliverables, with AA's 95% interval. | 1,252 | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
| AnalystAgent (AA run)AA's AnalystAgent score for analyst workflows. | 43.8% | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
| APEX-Agents (maintainers)APEX-Agents pass@1 from the maintainers, as Epoch AI republishes it. | 49.2% | Max effort | Mercor (via Epoch AI) | Oct 26, 2026 |
| GDPval-AAGDPval-AA Elo: AA's run of economically valuable knowledge-work tasks, graded pairwise, with AA's interval. | 1,353 | Claude Opus 4.7 (Max) | 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. | $10,937 | Andon Labs (via Epoch AI) | Oct 26, 2026 | |
| Capability beyond the chart | ||||
| AA-LCRAA long-context reasoning accuracy. | 78.7% | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
| ALE-BenchALE-Bench performance rating on long optimization contests, as Epoch AI republishes it. | 1,323 | Sakana AI (via Epoch AI) | Oct 26, 2026 | |
| ARC-AGI-2ARC-AGI-2 score from the ARC Prize maintainers, as Epoch AI republishes it. | 75.8% | Max effort | ARC Prize Foundation (via Epoch AI) | Oct 26, 2026 |
| Chess puzzles (Epoch)Share of chess puzzles solved, Epoch AI's run. | 41% | Max effort | Epoch AI | Oct 13, 2026 |
| CritPt (AA run)Share of CritPt research-level physics problems solved in AA's run. | 12% | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
| DTBenchDTBench accuracy, as Epoch AI republishes it. | 94.7% | 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. | 157 | Claude Opus 4.7 | Epoch AI | Oct 26, 2026 |
| FrontierMath Tier 4 (Epoch)Share of FrontierMath Tier 4 research math problems solved, Epoch AI's run. | 31.7% | Max effort | Epoch AI | Jun 10, 2026 |
| FrontierMath Tiers 1 to 3 (Epoch)Share of FrontierMath Tiers 1 to 3 problems solved, Epoch AI's run. | 70.2% | Max effort | Epoch AI | Jun 10, 2026 |
| GPQA Diamond (AA run)GPQA Diamond accuracy in AA's run. | 91.4% | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
| GPQA Diamond (Epoch)GPQA Diamond accuracy, best scorer, Epoch AI's run. | 86.4% | Max effort | Epoch AI | Aug 6, 2026 |
| Humanity's Last Exam (AA run)Share of Humanity's Last Exam questions answered correctly in AA's run. | 42.3% | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
| IFBench (AA run)Instruction-following accuracy on IFBench in AA's run. | 58.6% | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
| Intelligence IndexArtificial Analysis Intelligence Index: AA's composite of its own evaluation runs, 0 to 100 points. | 40.7 | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
| IT-Bench SRE (AA run)AA's IT-Bench SRE score for incident and reliability agents. | 46.7% | Claude Opus 4.7 (Max) | 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. | 52.2 | Max effort | Redwood Research (via Epoch AI) | Oct 26, 2026 |
| MMMU-Pro (AA run)Multimodal understanding accuracy on MMMU-Pro in AA's run. | 78.8% | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
| Mystery game puzzles (Epoch)Share of mystery game puzzles solved, Epoch AI's run. | 28% | Max effort | Epoch AI | Jul 25, 2026 |
| OTIS Mock AIME (Epoch)Share of OTIS Mock AIME 2024 to 2025 problems solved, Epoch AI's run. | 86.7% | Max effort | Epoch AI | Aug 6, 2026 |
| ProofBenchShare of ProofBench proofs graded correct, from Vals AI as Epoch AI republishes it. | 54% | Max effort | Vals AI (via Epoch AI) | Oct 26, 2026 |
| tau-Banking (AA run)AA's tau-Banking tool-use score. | 34.6% | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
| tau2-Bench (AA run)AA's tau2-Bench tool-use score. | 88.6% | Claude Opus 4.7 (Max) | 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. | 1,555 | High effort | LMArena (via Epoch AI) | Oct 26, 2026 |
| Domains | ||||
| EconomicsArtificial Analysis capability score for economics questions, 0 to 100 points. | 50 | Claude Opus 4.7 (Max) | Artificial Analysis | Oct 26, 2026 |
Routes, prices and uptime
Where Claude Opus 4.7 is offered, what each route charges, and how each endpoint is holding up.
Where it is offered
13 of 19 routes GILD tracks offer Claude Opus 4.7 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-4-7 | us./eu./jp./au./global. profiles; Active, EOL not sooner than Apr 16, 2027; tiers: Standard only; context / output 1M / 128K | Amazon Web Services, Models at a glanceAmazon Web Services, Claude Opus 4.7 |
| Claude Code | Available | claude-opus-4-7 | By full model name on the Anthropic API, or provider ARN, version or deployment name; aliases resolve per provider; fast mode removed July 24, 2026; runs with the 1M window by default (page read Oct 28, 2026) | Anthropic, Model configurationAnthropic, Speed up responses with fast mode |
| Claude on Google Cloud (Anthropic managed) | Available | claude-opus-4-7 | Claude API model IDs (dated IDs use a hyphen) | Anthropic, Claude Opus 4.7Anthropic, Claude Models on Google Cloud (Anthropic managed) |
| Claude Platform on AWS | Available | claude-opus-4-7 | Same ID as the Claude API | Anthropic |
| Cursor | Available | available, hidden by default; also lists a stale 'Opus 4.7 (fast mode)' row; Premium plan or higher, API list price; stale fast-mode row conflicts with Anthropic's removal | Anysphere (Cursor) | |
| Databricks | Available | databricks-claude-opus-4-7 | available | Databricks, Databricks-hosted inferenceDatabricks, Detailed list of models supported by Databricks Foundation Model APIs |
| The maker's own API | Available | claude-opus-4-7 | context / max output 1M / 128K; status per deprecations table | Anthropic, Claude Opus 4.7Anthropic, Model deprecations |
| GitHub Copilot | Retired | not statedretired picker label Claude Opus 4.7 | retired 2026-10-02 | GitHub, Supported AI models in GitHub Copilot |
| GitHub Models | Retired | not applicableservice retired | service retired July 30, 2026 | GitHub, GitHub Models |
| Google Cloud Vertex / Agent Platform (Google managed) | Available | claude-opus-4-7 (GA) | retirement not sooner than Apr 16, 2027; input / output 1,000,000 / 128,000 | Google, Anthropic's Claude on Google Cloud modelsGoogle, Anthropic's Claude Opus 4.7 on Google CloudAnthropic |
| Microsoft Foundry | Available | claude-opus-4-7 | deployment name defaults to model ID; hosted on Anthropic only; context 1M; no Message Batches API | AnthropicMicrosoft Learn |
| OpenCode | Available | claude-opus-4-7 | OpenCode Zen gateway, Anthropic Messages endpoint | Anomaly (OpenCode), ModelsOpenCode (Anomaly) |
| OpenRouter | Available | anthropic/claude-opus-4.7 | context / max completion 1,000,000 / 128,000 | OpenRouter |
| Snowflake Cortex | Available | claude-opus-4-7 | Regions: Cross Cloud (Any Region); AWS US (Cross-Region); AWS EU (Cross-Region). Context 1,000,000; maximum output 128,000 tokens. | Snowflake |
| Windsurf / Devin | Available | claude-opus-4-7-highclaude-opus-4-7-lowclaude-opus-4-7-maxclaude-opus-4-7-mediumclaude-opus-4-7-xhigh | available | Cognition (Devin, formerly Windsurf), AI ModelsCognition (Devin, formerly Windsurf), Compliance and Availability |
Not offered on 1 route: Antigravity.
3 routes do not say: Codex, Gemini CLI and Grok Build.
What each of these 4 routes' pages say, with sources
| Route | Status | Model ID | Limits and lifecycle | Sources |
|---|---|---|---|---|
| Antigravity | Not offered | not listed; Gemini CLI serves Gemini models only | ||
| 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 $5 / $25 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.
| Route | Standard, in / out | Cache read | Other rates | Source, or uptime (1 day / 30 min) and limits |
|---|---|---|---|---|
| Claude APIMakerLowest | $5 / $25 | Anthropic, Oct 26, 2026 | ||
| Artificial Analysis price record | $5 / $25 | $0.5 | Blended $10, 3 input : 1 output, no cacheBlended $3.85, 7 cache-hit : 2 input : 1 outputCache write $6.25 | Artificial Analysis, Oct 26, 2026 |
Lineup
Anthropic's 14 releases in 4 families, oldest to newest along each tier, with list price and speed. Claude Opus 4.7 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
- This page4.7Legacy. 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
- 5.5Current. 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
Products
We cover 4 products that offer Claude Opus 4.7 today: 3 subscriptions and 1 API.
Through a subscription
- 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 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.
Through an API
Comparisons
GILD comparisons that name Claude Opus 4.7, then those of the clouds and APIs that serve it.
- Amazon Bedrock vs Claude API: Buying Claude Through AWS or From AnthropicCompares routes that serve Claude Opus 4.7
- Amazon Bedrock vs Microsoft Foundry: Which Cloud AI Platform Fits Your Stack?Compares routes that serve Claude Opus 4.7
- Claude API vs Gemini API: Which Model Platform Fits Your Workloads?Compares routes that serve Claude Opus 4.7
- Claude API vs OpenAI API: Top Scores or Lower Cost per Task?Compares routes that serve Claude Opus 4.7
- DeepSeek API vs Claude API: Price per Task or Controls and Residency?Compares routes that serve Claude Opus 4.7
- DeepSeek API vs OpenRouter: Buy DeepSeek From DeepSeek, or From Another Host?Compares routes that serve Claude Opus 4.7
- Gemini API vs Amazon Bedrock: One Model Family or a Model Marketplace?Compares routes that serve Claude Opus 4.7
- Gemini API vs Gemini Enterprise Agent Platform: Which Route to Gemini?Compares routes that serve Claude Opus 4.7
- Gemini Enterprise Agent Platform vs Microsoft Foundry: Google Cloud or Azure for Models and AgentsCompares routes that serve Claude Opus 4.7
- LiteLLM vs OpenRouter: Run Your Own Gateway or Rent One?Compares routes that serve Claude Opus 4.7
- OpenRouter vs Portkey: Rent Model Access or Run a Governed Gateway?Compares routes that serve Claude Opus 4.7
- Together AI vs OpenRouter: One Open-Model Host or a Router Across HostsCompares routes that serve Claude Opus 4.7
What practitioners report
Strongest on Speed, weakest on Reliability.
Each figure is the share of accounts naming Claude Opus 4.7 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. | 57% | 12 favorable, 9 not, 21 authors |
| Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track. | 50% | 4 favorable, 4 not, 8 authors |
| Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs. | 50% | 4 favorable, 4 not, 7 authors |
| Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers. | 29% | 4 favorable, 10 not, 14 authors |
| CostWhat the work costs: price per task, token use, and what caching and batch save. | 50% | 7 favorable, 7 not, 13 authors |
| SpeedResponse time, time to first token, and throughput. | 63% | 5 favorable, 3 not, 8 authors |
| ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked. | 18% | 2 favorable, 9 not, 11 authors |
Every model on these seven axes
| Axis | Claude Opus 4.7 | Claude Haiku 5.5 | Claude Sonnet 5.5 | Claude Opus 5.5 | Claude Fable 5.1 | Claude Opus 5 | Claude Sonnet 5 | Claude Fable 5 | Claude Opus 4.8 | 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 | 57%12 favorable, 9 not, 21 authors | 73%19 favorable, 7 not, 26 authors | 64%14 favorable, 8 not, 22 authors | 68%17 favorable, 8 not, 25 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 | 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 | 50%4 favorable, 4 not, 8 authors | 67%6 favorable, 3 not, 9 authors | 40%4 favorable, 6 not, 10 authors | 46%6 favorable, 7 not, 13 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 | 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 | 50%4 favorable, 4 not, 7 authors | 29%2 favorable, 5 not, 7 authors | 60%3 favorable, 2 not, 5 authors | 80%8 favorable, 2 not, 10 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 | 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 | 29%4 favorable, 10 not, 14 authors | 25%2 favorable, 6 not, 8 authors | 38%5 favorable, 8 not, 13 authors | 38%6 favorable, 10 not, 16 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 | 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 | 50%7 favorable, 7 not, 13 authors | 69%20 favorable, 9 not, 29 authors | 45%10 favorable, 12 not, 22 authors | 56%15 favorable, 12 not, 27 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%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 | 63%5 favorable, 3 not, 8 authors | 74%14 favorable, 5 not, 19 authors | 88%14 favorable, 2 not, 16 authors | 46%6 favorable, 7 not, 13 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 | 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 | 18%2 favorable, 9 not, 11 authors | 20%1 favorable, 4 not, 5 authors | 18%2 favorable, 9 not, 11 authors | 13%1 favorable, 7 not, 8 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 | 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 68 accounts behind Claude Opus 4.7's figures
GILD searched Hacker News, GitHub, Reddit, X, Artificial Analysis, OpenRouter, Vals AI and the web for accounts that name Claude Opus 4.7.
Quality and reasoning 57%
- Favorable
Opus 4.7 is more strategic, more intelligent, and has a higher intelligence floor than 4.6 or 4.5
Comment on: Claude Opus 4.7. gertlabs, Hacker News commenter publishing a private reasoning benchmark, self-described, Apr 16, 2026. Opus 4.7 on Gertlabs' private reasoning and agentic coding suite.
- Favorable
The best-performing model (Muse Spark) reaches 82.2%, followed by Claude Opus 4.7 (79.1%)
MCP-Atlas evaluation of 20 frontier models. Chaithanya Bandi, paper author, self-described, May 19, 2026. Claude Opus 4.7 (claude-opus-4-7, adaptive, effort=max) among 20 models on 1,000 MCP tasks.
- Unfavorable
Opus 4.7 on the max setting still gets lost and chokes on a lot of my tasks
Comment on: Changes to GitHub Copilot individual plans. Aurornis, Hacker News commenter, self-described, Apr 22, 2026. Opus 4.7 on the max setting in a medium-size codebase.
- Favorable
My evals[1] show that Opus 4.7 and GPT 5.5 are very comparable in terms of generation quality
Comment on: Show HN: AI CAD Harness. ponyous, Hacker News commenter, self-described, May 1, 2026. Opus 4.7 against GPT 5.5 in the commenter's CAD-generation evals.
- Favorable
Opus 4.7 Max 1M has been a very significant jump in performance for me
Comment on: Kimi K2.6: Advancing open-source coding. Topfi, Hacker News commenter, self-described, Apr 20, 2026. Opus 4.7 Max 1M.
- Unfavorable
Substantially worse at following instructions and overoptimized for maximizing token usage
Comment on: DeepSeek v4. spaceman_2020, Hacker News commenter, self-described, Apr 24, 2026. Opus 4.7 against Opus 4.6.
- Unfavorable
it doesnt follow the CLAUDE.md instruction, it hallucinates a lot, by default it makes things up when it can't find the answer to something
Comment on: OpenAI releases GPT-5.5 and GPT-5.5 Pro in the API. robertwt7, Hacker News commenter, self-described, Apr 24, 2026. Opus 4.7 against GPT 5.5 in Codex.
- Unfavorable
I think that Opus 4.7 was a big step backwards
Comment on: Anthropic surpasses OpenAI to become most valuable AI startup. epistasis, Hacker News commenter, self-described, May 30, 2026. Opus 4.7 in Claude Code.
- Unfavorable
4.7 hit usage limits faster, didn't do anything obviously better, and had more annoying behaviors in other aspects
Comment on: Agents for financial services and insurance. philipkglass, Hacker News commenter, self-described, May 6, 2026. Opus 4.7 for two days in Claude Code, then back to claude-opus-4-6.
- Favorable
Codex w/ gpt-5.5 seems faster but maybe just a bit below Opus 4.7 quality
Comment on: The last six months in LLMs in five minutes. nijave, Hacker News commenter, self-described, May 19, 2026. Claude Code Opus 4.7 on xhigh effort.
- Favorable
opus 4.7 is really good compared to everything else
Comment on: I think Anthropic and OpenAI have found product-market fit. strix_varius, Hacker News commenter, self-described, May 28, 2026. Opus 4.7 at work, paid by the employer.
- Favorable
instead of just implementing the template, 4.7 notices a bug in the template as well, suggests some code design improvements
Comment on: Ask HN: Can you tell the difference between Claude Sonnet and Opus?. SyneRyder, Hacker News commenter, self-described, Apr 29, 2026. Opus 4.7 refactoring an MCP code template.
- Favorable
opus was the only model to push back against the spec on the hardest challenge
Comment on: Running local LLMs offline on a ten-hour flight. sleepyeldrazi, Hacker News commenter, self-described, Apr 27, 2026. Opus 4.7 with the 1M context window against open-weights models on 8 programming tests.
- Favorable
As a counter opinion, I find Opus 4.7 to be great. It is my default model.
Comment on: Opus 4.7 is unusable. I am tired of the apologies. uberman, Hacker News commenter, self-described, May 6, 2026. Opus 4.7 as the default model.
- Favorable
Claude Opus 4.7 (Max) is amongst the leading models in intelligence
Claude Opus 4.7 (max) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking firm, self-described, Oct 26, 2026. Claude Opus 4.7 (Max) on the Artificial Analysis Intelligence Index and API speed tests.
- Favorable
Claude Opus 4.7 performs excellently on coding tasks, placing first on Terminal-Bench 2.0
Claude Opus 4.7 Benchmarks, Cost and Capabilities | Vals AI. Vals AI, independent model evaluation company, self-described, Apr 16, 2026. Claude Opus 4.7 at max compute effort on Vals AI benchmarks.
- Favorable
Opus 4.7 blew its predecessors out of the water by achieving 98.5% accuracy on the same visual acuity benchmark
Smaller Bites, Bigger Meals: What We Learned Running Opus 4.7 in Offensive Workflows. Albert Ziegler, Head of AI at XBOW, Apr 16, 2026. Opus 4.7, pre-release access, powering XBOW's autonomous pentesting benchmark.
- Favorable
Claude Opus 4.7 finds more real bugs, produces more actionable feedback, and reasons across files better than anything we've tested before
What Claude Opus 4.7 means for AI code review. Juan Pablo Flores, writing on the CodeRabbit engineering blog, self-described, Apr 16, 2026. Claude Opus 4.7 in CodeRabbit's production code-review harness, 100 evaluation points.
- Unfavorable
I'm giving this one to Qwen 3.6. Opus managed to mess up the bicycle frame!
Qwen3.6-35B-A3B on my laptop drew me a better pelican than Claude Opus 4.7. Simon Willison, developer and blogger, self-described, Apr 16, 2026. Claude Opus 4.7, including thinking_level max, on SVG drawing prompts.
- Favorable
equivalence, footprint risk, maintainability on shippable-looking patches, mean task time
Opus 4.7 vs Old Opus 4.6 vs New Opus 4.6. Ben, Founder of Stet, self-described, Apr 17, 2026. Opus 4.7 at high effort in Claude Code on 28 historical Zod tasks, against two Opus 4.6 snapshots.
- Favorable
This is a genuine capability release.
Opus 4.7: Smarter, Stricter, Hungrier. paddo, author of the paddo.dev blog, self-described, Apr 17, 2026. Opus 4.7 in Claude Code at the xhigh default and on the API.
- Unfavorable
Opus 4.7 hallucinates FREQUENTLY compared to Opus 4.6
[BUG] Opus 4.7 Hallucinations. tomtokitajr, GitHub issue author, self-described, Apr 18, 2026. Opus 4.7 in Claude Code 2.1.112 on multi-step project tasks.
- Unfavorable
A big problem with Opus 4.7 was its hallucinations.
wh on Opus 4.7 hallucinations. wh (nrehiew_), engineer posting on X, self-described, May 28, 2026. Opus 4.7 against Opus 4.8 reported benchmarks.
- Unfavorable
by the end deepseek v4 pro was beating opus 4.7 6/10 times on our internal evals
Ahmad Awais on DeepSeek against Opus 4.7 in Command Code. Ahmad Awais, Founder and CEO of Command Code, May 3, 2026. Opus 4.7 against DeepSeek V4 Pro on Command Code's internal evals.
Tool use and structured output 50%
- Unfavorable
8/10 had non-conforming top-level shape; 2/10 conformed.
Batch API: tool_use input wrapped in $PARAMETER_NAME placeholder key (claude-opus-4-7). ffishman, GitHub issue author, self-described, May 28, 2026. claude-opus-4-7 on the Message Batches API with forced tool_choice.
- Favorable
in agentic sessions with tools, it IS the best, as advertised
Comment on: Claude Opus 4.7. gertlabs, Hacker News commenter publishing a private reasoning benchmark, self-described, Apr 16, 2026. Opus 4.7 on Gertlabs' private reasoning and agentic coding suite.
- Favorable
the newer GPT-5.5 and Claude Opus 4.7 almost eliminate this mode, with early-termination rates of only 3.6% and 3.8%
MCP-Atlas evaluation of 20 frontier models. Chaithanya Bandi, paper author, self-described, May 19, 2026. Claude Opus 4.7 (claude-opus-4-7, adaptive, effort=max) among 20 models on 1,000 MCP tasks.
- Unfavorable
It's shocking how inefficient it is with tasks like bash tool usage and web searching, delegating them to a dozen subagents only to get stuck and never return until you esc and intervene.
Comment on: Microsoft starts canceling Claude Code licenses. o10449366, Hacker News commenter, self-described, May 22, 2026. Opus 4.7 in Claude Code over three months, about $40K in token-equivalent spend.
- Favorable
Task Inference, Task Evaluation, Task Adherence, tool calling, all do very well on my evals.
Comment on: Show HN: State of the Art of Coding Models, According to Hacker News Commenters. Topfi, Hacker News commenter, self-described, May 3, 2026. Opus 4.7 via the API with other harnesses, and in Claude Code.
- Favorable
I gave Opus access to a repl (pyrasite-ng) in a running Python process and it managed to find an 8 year old "memory leak"
Comment on: The last six months in LLMs in five minutes. nijave, Hacker News commenter, self-described, May 19, 2026. Claude Code Opus 4.7 on xhigh effort.
- Unfavorable
thinking + response_format: ❌ (400)
[Bug]: Vertex Anthropic: response_format + thinking returns 400 on vertex_ai/claude-opus-4-7. gabrielafsantos, GitHub issue author, self-described, Apr 23, 2026. vertex_ai/claude-opus-4-7 through LiteLLM with adaptive thinking and a Pydantic response_format.
- Favorable
I've been using Claude Opus 4.7 with Chrome MCP, and it has worked successfully about 95% of the time.
Comment on: CAPTCHAs can still detect AI agents. cute_boi, Hacker News commenter, self-described, May 29, 2026. Claude Opus 4.7 with the Chrome MCP server.
- Unfavorable
Opus 4.7 already ignores a 720-byte CLAUDE.md telling it to use tidewave (a Rails MCP server with 6 tools) for db queries
Comment on: Show HN: Agent-skills-eval – Test whether Agent Skills improve outputs. reedlaw, Hacker News commenter, self-described, May 7, 2026. Opus 4.7 in Claude Code with a Rails MCP server named in CLAUDE.md.
Long context 50%
- Unfavorable
Even Anthropic's own model card shows context handling regressions
Comment on: Claude Opus 4.7. gertlabs, Hacker News commenter publishing a private reasoning benchmark, self-described, Apr 16, 2026. Opus 4.7 on Gertlabs' private reasoning and agentic coding suite.
- Favorable
Unlike 4.6, I have found the model to degrade far less beyond 120k, even 600k can be relied upon.
Comment on: Show HN: State of the Art of Coding Models, According to Hacker News Commenters. Topfi, Hacker News commenter, self-described, May 3, 2026. Opus 4.7 via the API with other harnesses, and in Claude Code.
- Favorable
especially in tasks beyond 120k token where I'd argue it is now the most reliable model in continued task adherence and tool calling without compaction
Comment on: Kimi K2.6: Advancing open-source coding. Topfi, Hacker News commenter, self-described, Apr 20, 2026. Opus 4.7 Max 1M.
- Favorable
opus 4.7 i could stretch to around 400k the dumb zone started
Comment on: Don't trust large context windows. pdantix, Hacker News commenter, self-described, Jun 14, 2026. Opus 4.7 against Opus 4.5, 4.6 and 4.8 in long sessions.
- Unfavorable
Opus 4.7 is unusable past 200k conversation length
Comment on: Dynamic Workflows in Claude Code. afro88, Hacker News commenter, self-described, May 28, 2026. Opus 4.7 in Claude Code long conversations.
- Unfavorable
it causes opus 4.7 to lose all memory every time I hit a compaction step
Comment on: Changes to GitHub Copilot individual plans. WhiteDawn, Hacker News commenter, self-described, Apr 22, 2026. Opus 4.7 in GitHub Copilot's local agent and in opencode.
- Unfavorable
I'm using Opus 4.7 w/ the 1M context option on the vibrating mesh nebulizer repo and have hit compacting pretty often
Comment on: Text-to-CAD. david_mchale, Hacker News commenter, self-described, May 4, 2026. Opus 4.7 with the 1M context option on an OpenSCAD repo.
- Favorable
One of the most impressive capabilities, and the one that benefits most from the expanded context window, is the model's ability to connect findings across files.
What Claude Opus 4.7 means for AI code review. Juan Pablo Flores, writing on the CodeRabbit engineering blog, self-described, Apr 16, 2026. Claude Opus 4.7 in CodeRabbit's production code-review harness, 100 evaluation points.
Developer experience 29%
- Unfavorable
anthropic.claude-opus-4-7 is not available for this account.
Comment on: Claude Opus 4.7. ramonga, Hacker News commenter, self-described, Apr 16, 2026. Claude Opus 4.7 on Amazon Bedrock.
- Unfavorable
it also forgets things it was asked several times, even just minutes after being reminded again
Comment on: Reverse Engineering SimTower. appplication, Hacker News commenter, self-described, May 1, 2026. Opus 4.7 in the commenter's usual coding workflow.
- Favorable
it's good code if I tell it to follow my existing code's structures
Comment on: Why Does Everyone Hate AI?. danlugo92, Hacker News commenter, self-described, Jun 25, 2026. Claude Opus 4.7 for daily coding.
- Unfavorable
Personality-wise it's the worst of AI, "it's not x, it's y", strong short sentences, in general a bulshitty vibe
Comment on: An update on recent Claude Code quality reports. cube2222, Hacker News commenter, self-described, Apr 23, 2026. Opus 4.7 in Claude Code, rolled back to Opus 4.6.
- Unfavorable
Opus 4.7 is very rough to work with.
Comment on: An update on recent Claude Code quality reports. ramoz, Hacker News commenter, self-described, Apr 23, 2026. Opus 4.7 on long-horizon work, rolled back to claude-opus-4-6[1m].
- Unfavorable
Not having these dials limits utility for cases like synthetic data generation, natural language QA and many more.
Claude Opus 4.7 API removes sampling parameters. curioussquirrel, Hacker News commenter, self-described, Apr 19, 2026. Claude Opus 4.7 on the API.
- Unfavorable
CLAUDE_CODE_DISABLE_ADAPTIVE_THINKING=1 even though Opus 4.7 ignores it
Comment on: Anonymous request-token comparisons from Opus 4.6 and Opus 4.7. matheusmoreira, Hacker News commenter, self-described, Apr 19, 2026. Opus 4.7 in Claude Code with the 1M window at max effort.
- Favorable
It feels much better to do planning and strategy and architecture etc. with Opus 4.7 than GPT-5.5.
Comment on: Claude Opus 4.8. suprfnk, Hacker News commenter, self-described, May 28, 2026. Opus 4.7 against GPT-5.5 for planning and architecture.
- Unfavorable
I have tried without success to make it more concise
Comment on: Opus 4.7 is unusable. I am tired of the apologies. uberman, Hacker News commenter, self-described, May 6, 2026. Opus 4.7 as the default model.
- Unfavorable
For sure Opus 4.7 is more chatty and talkative
Comment on: Anonymous request-token comparisons from Opus 4.6 and Opus 4.7. carlovalenti, Hacker News commenter, self-described, Apr 29, 2026. Opus 4.7 in the Claude web interface with adaptive thinking on, Pro plan.
- Unfavorable
We also encountered a relatively large number of safety refusals on Claude Opus 4.7
Claude Opus 4.7 Benchmarks, Cost and Capabilities | Vals AI. Vals AI, independent model evaluation company, self-described, Apr 16, 2026. Claude Opus 4.7 at max compute effort on Vals AI benchmarks.
- Unfavorable
even at its highest setting, 4.7's "bite size" still lagged very far behind other models' on our benchmarks
Smaller Bites, Bigger Meals: What We Learned Running Opus 4.7 in Offensive Workflows. Albert Ziegler, Head of AI at XBOW, Apr 16, 2026. Opus 4.7, pre-release access, powering XBOW's autonomous pentesting benchmark.
- Favorable
Opus 4.7 is remarkably good at interpreting imprecise prompts.
What Claude Opus 4.7 means for AI code review. Juan Pablo Flores, writing on the CodeRabbit engineering blog, self-described, Apr 16, 2026. Claude Opus 4.7 in CodeRabbit's production code-review harness, 100 evaluation points.
- Unfavorable
Anthropic documents that Claude Opus 4.7 and later and the Claude 5 models return a 400 for non-default `temperature`, `top_p` or `top_k`.
[BUG] ConversationSimulator never detects the goal with Claude Opus 4.7+ / Claude 5 user models. pcbeingused333, GitHub issue author, self-described, Oct 16, 2026. Claude Opus 4.7 and later as the user model in MLflow's ConversationSimulator.
- Favorable
Opus 4.7 is happy to let me lead, and to take time to discuss, rather than barging ahead
Jeremy Howard on Opus 4.7. Jeremy Howard, founding CEO of Answer.AI and co-founder of fast.ai, Apr 17, 2026. Opus 4.7 in interactive work.
Cost 50%
- Unfavorable
~20% more expensive then new 4.6 (because new 4.6 is thinking less)
Comment on: Claude Opus 4.7 costs 20–30% more per session. bisonbear, Hacker News commenter, self-described, Apr 17, 2026. Opus 4.7 against old and new Opus 4.6 on 28 coding tasks.
- Favorable
Notably the cost of reasoning has been cut almost in half from 4.6 to 4.7.
Comment on: Anonymous request-token comparisons from Opus 4.6 and Opus 4.7. andai, Hacker News commenter, self-described, Apr 18, 2026. Opus 4.7 against Opus 4.5 and 4.6 on Artificial Analysis token counts.
- Favorable
Opus 4.7 might on average arrive at the answer with fewer tokens spent, even with the additional tokenizer overhead
Comment on: Claude Token Counter, now with model comparisons. Aurornis, Hacker News commenter, self-described, Apr 20, 2026. Opus 4.7 with its new tokenizer.
- Favorable
$100 a month, or more, to get Opus 4.7 is well worth it for a western developer
Comment on: Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving. SwellJoe, Hacker News commenter, self-described, Apr 20, 2026. Opus 4.7 on a paid Claude plan for software development.
- Unfavorable
sending 3-4 messages to Opus 4.7 for this blew through my $20 plan limits and consumed $10 of extra usage on top
Comment on: Claude Code to be removed from Anthropic's Pro plan?. user34283, Hacker News commenter, self-described, Apr 21, 2026. Opus 4.7 on the $20 Claude plan, debugging an iOS app.
- Unfavorable
Opus 4.7 has effectively made Claude Max 5x into Max 2.5x
Comment on: Ask HN: Why Opus4.6 was silently removed from Claude Code?. kivle, Hacker News commenter, self-described, Apr 22, 2026. Opus 4.7 on Claude Max 5x.
- Unfavorable
even with Opus 4.7 I can often go through my entire 5-hour credit limit just trying to get it to converge on a reasonable plan
Comment on: Changes to GitHub Copilot individual plans. Aurornis, Hacker News commenter, self-described, Apr 22, 2026. Opus 4.7 on the max setting in a medium-size codebase.
- Favorable
GPT 5.5 is slower and costs sooo much more in my harness
Comment on: Show HN: AI CAD Harness. ponyous, Hacker News commenter, self-described, May 1, 2026. Opus 4.7 against GPT 5.5 in the commenter's CAD-generation evals.
- Unfavorable
I don't need Opus 4.7, even for my complex programming tasks. It costs over 10x other models available that still give good enough answers.
Comment on: I think Anthropic and OpenAI have found product-market fit. RevEng, Hacker News commenter, self-described, May 28, 2026. Opus 4.7 against smaller models for complex programming.
- Unfavorable
but particularly expensive when comparing to other models of similar price
Claude Opus 4.7 (max) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking firm, self-described, Oct 26, 2026. Claude Opus 4.7 (Max) on the Artificial Analysis Intelligence Index and API speed tests.
- Favorable
Given the same token budget, Opus 4.7 gets further.
Smaller Bites, Bigger Meals: What We Learned Running Opus 4.7 in Offensive Workflows. Albert Ziegler, Head of AI at XBOW, Apr 16, 2026. Opus 4.7, pre-release access, powering XBOW's autonomous pentesting benchmark.
- Unfavorable
this token inflation means we can expect it to be around 40% more expensive
Claude Token Counter, now with model comparisons. Simon Willison, developer and blogger, self-described, Apr 20, 2026. Claude Opus 4.7 against Opus 4.6 in the Claude token counting API.
- Favorable
4.7 is cheaper per task than March 4.6 ($8.11 vs $8.93)
Opus 4.7 vs Old Opus 4.6 vs New Opus 4.6. Ben, Founder of Stet, self-described, Apr 17, 2026. Opus 4.7 at high effort in Claude Code on 28 historical Zod tasks, against two Opus 4.6 snapshots.
- Unfavorable
A workload that cost you $100/day on 4.6 at medium effort could easily run $150-180/day on 4.7 at xhigh, for a +13% benchmark lift.
Opus 4.7: Smarter, Stricter, Hungrier. paddo, author of the paddo.dev blog, self-described, Apr 17, 2026. Opus 4.7 in Claude Code at the xhigh default and on the API.
- Favorable
Even if I pay $1,000 a month for API usage ($12,000 a year) that's still a steal compared to hiring humans
Alex Finn on Opus 4.7 with OpenClaw. Alex Finn, X poster running OpenClaw agents, self-described, Apr 20, 2026. Opus 4.7 with OpenClaw through the API.
Speed 63%
- Favorable
it averages 149s per task, roughly twice the wall-clock cost of Claude Opus 4.6 and Opus 4.7 for comparable accuracy
MCP-Atlas evaluation of 20 frontier models. Chaithanya Bandi, paper author, self-described, May 19, 2026. Claude Opus 4.7 (claude-opus-4-7, adaptive, effort=max) among 20 models on 1,000 MCP tasks.
- Favorable
Opus 4.7 is also quite fast.
Comment on: DeepSeek v4. gertlabs, Hacker News commenter publishing a private reasoning benchmark, self-described, Apr 24, 2026. Opus 4.7 on Gertlabs' one-shot coding time measurements.
- Favorable
For Opus 4.7, Bedrock is the clear winner in TPS by leaps
Comment on: OpenAI models coming to Amazon Bedrock: Interview with OpenAI and AWS CEOs. dannyw, Hacker News commenter, self-described, Apr 29, 2026. Opus 4.7 across providers on Artificial Analysis.
- Unfavorable
grok was also the fastest+cheapest model, claude was slowest and priciest
Comment on: Grok 4.3. michaelbuckbee, Hacker News commenter, self-described, May 1, 2026. Opus 4.7 against Grok 4.3 and GPT 4.1 in a tone eval.
- Unfavorable
I found Opus 4.7 to be slow and wasteful with token usage.
Comment on: Microsoft starts canceling Claude Code licenses. o10449366, Hacker News commenter, self-described, May 22, 2026. Opus 4.7 in Claude Code over three months, about $40K in token-equivalent spend.
- Unfavorable
Opus 4.7 is frustratingly slow (and, at least in my experience, much slower than 4.5 was)
Comment on: Claude Opus 4.8. insane_dreamer, Hacker News commenter, self-described, May 28, 2026. Opus 4.7 against Opus 4.5.
- Unfavorable
At 52 tokens per second, Claude Opus 4.7 (Max) is notably slow
Claude Opus 4.7 (max) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking firm, self-described, Oct 26, 2026. Claude Opus 4.7 (Max) on the Artificial Analysis Intelligence Index and API speed tests.
- Favorable
Opus 4.7 solves more environments after the same amount of time has elapsed
Smaller Bites, Bigger Meals: What We Learned Running Opus 4.7 in Offensive Workflows. Albert Ziegler, Head of AI at XBOW, Apr 16, 2026. Opus 4.7, pre-release access, powering XBOW's autonomous pentesting benchmark.
- Favorable
Even on complex tasks, the overall velocity is noticeably faster than previous models.
What Claude Opus 4.7 means for AI code review. Juan Pablo Flores, writing on the CodeRabbit engineering blog, self-described, Apr 16, 2026. Claude Opus 4.7 in CodeRabbit's production code-review harness, 100 evaluation points.
- Favorable
finishes the full 28-task run faster (1h 30m vs 1h 36m)
Opus 4.7 vs Old Opus 4.6 vs New Opus 4.6. Ben, Founder of Stet, self-described, Apr 17, 2026. Opus 4.7 at high effort in Claude Code on 28 historical Zod tasks, against two Opus 4.6 snapshots.
Reliability 18%
- Unfavorable
My systems are hitting exponential delay retries, so this might not get better because retries overload things again.
Comment on: Elevated error rates on Opus 4.7. gopalv, Hacker News commenter, self-described, May 15, 2026. Sonnet and Opus 4.7 during the elevated error rates incident on Opus 4.7.
- Unfavorable
Suddenly our Opus 4.7 access was removed from Bedrock ( The quota was set to 0 suddenly).
Tell HN: Claude Opus 4.7 quota suddenly changed to 0 TPM in Bedrock. sarathyweb, Hacker News commenter, self-described, May 1, 2026. Claude Opus 4.7 on Amazon Bedrock, us-east-1.
- Unfavorable
I found switching from Opus 4.7 to be completely painless and in fact, due to the reliability of Anthropic's API, less of a friction
Comment on: DeepSeek V4 – almost on the frontier. gmerc, Hacker News commenter, self-described, May 2, 2026. Opus 4.7 through Anthropic's API, replaced by DeepSeek V4.
- Unfavorable
I for the first time saw true, reproducible, incredibly frustrating regressions in model output when using Claude Code
Comment on: Show HN: State of the Art of Coding Models, According to Hacker News Commenters. Topfi, Hacker News commenter, self-described, May 3, 2026. Opus 4.7 via the API with other harnesses, and in Claude Code.
- Favorable
I sometimes have 2 or 3 instances chugging along with Opus 4.7 or Sonnet 4.6 and have never had it be down or error out due to usage limits
Comment on: OpenAI models coming to Amazon Bedrock: Interview with OpenAI and AWS CEOs. InvidFlower, Hacker News commenter, self-described, Apr 30, 2026. Claude Code on Amazon Bedrock with Opus 4.7 or Sonnet 4.6.
- Favorable
Opus 4.7 with high thinking, with a $100 Max subscription, and haven't been rate limited yet
Comment on: Uber torches 2026 AI budget on Claude Code in four months. insane_dreamer, Hacker News commenter, self-described, May 2, 2026. Opus 4.7 with high thinking on a $100 Max subscription.
- Unfavorable
It appears that Opus 4.7 has been nerfed already. Can't get any sensible results since yesterday.
Comment on: An update on recent Claude Code quality reports. varispeed, Hacker News commenter, self-described, Apr 24, 2026. Opus 4.7.
- Unfavorable
Opus 4.7 went through a major degradation a few weeks ago (way more hallucinations and rabbit holes than usual)
Comment on: Microsoft starts canceling Claude Code licenses. whiplash451, Hacker News commenter, self-described, May 23, 2026. Opus 4.7.
- Unfavorable
I've hit the limiter with one single prompt now on Opus 4.7
Comment on: Claude Token Counter, now with model comparisons. Esophagus4, Hacker News commenter, self-described, Apr 20, 2026. Opus 4.7 on a Claude subscription.
- Unfavorable
Error: claude-opus-4-7[1m] is temporarily unavailable
Comment on: An update on recent Claude Code quality reports. bashtoni, Hacker News commenter, self-described, Apr 24, 2026. Opus 4.7 with the 1M window in Claude Code auto mode.
- Unfavorable
bubbles every 529 `overloaded_error` straight to the user as a chat failure
Dispatcher: retry + fall back to Opus 4.6 on 529 overloaded_error. 2by4-analytics, GitHub issue author, self-described, May 20, 2026. claude-opus-4-7 called directly from a chat dispatcher during the May 20 elevated-errors incident on Claude Opus 4.7.