Cost
$0.23per task
Cost per task. One Intelligence Index task at list price, every token counted. Run at reasoning on.
Claude Haiku model by Anthropic
Claude Haiku 4.5
An earlier Claude Haiku release, listed by Anthropic as a legacy model that is still available.
Where it sits in Anthropic's lineup
- Claude HaikuAnthropic's small, fast Claude model family for high-volume, latency-sensitive work.You are on Claude Haiku 4.5. Current:Claude Haiku 5.5
- Claude SonnetAnthropic's balanced Claude model family.Claude Sonnet 5.5
- Claude OpusAnthropic's high-capability Claude model family.Claude Opus 5.5
- Claude FableAnthropic's Claude family for demanding reasoning and long-horizon agentic work.Claude Fable 5.1
- Offered in
- 4 products
- Made by
- Anthropic
- Family
- Claude Haiku, version 4.5
- Released
- Oct 15, 2025 Legacy
- Lifecycle
- Active. Its earliest retirement date, Oct 15, 2026, has passed with no retirement date set, per Anthropic.
- Claude app: Out of the model selector on the Free, Pro and Max plans from Oct 29, 2026, replaced by Claude Haiku 5.5. Claude Code, the Team and Enterprise plans and the API keep it, per Anthropic.
- Amazon Bedrock: Active, with no end-of-life date set, per AWS.
- Google Cloud Vertex AI (Google managed): Retirement not sooner than Dec 7, 2026, per Google Cloud.
- Microsoft Foundry: GA, hosted on Azure and on Anthropic infrastructure, per Microsoft.
- GitHub Copilot: Generally available, per GitHub.
- In its family
- Release 1 of 2 in Claude Haiku. The newest is Claude Haiku 5.5.
Strengths and weaknesses
Compare with other models Up to 3 beside Claude Haiku 4.5
- Claude Haiku 4.5
Suggested comparisons
The models a buyer weighs against Claude Haiku 4.5, picked on list price and on Artificial Analysis's Intelligence Index of overall quality. Add one to draw it beside Claude Haiku 4.5.
Claude Haiku 4.5
Ranked against the 40 current releases on this chart, Claude Haiku 4.5's best rank is 8th of 9 on Instruction following. Math is Epoch AI's run on OTIS Mock AIME 2024-2025, marked on the chart. It ranks lowest on Multimodal, 25th of 25 and Science, 25th of 25. Agentic coding and Computer 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 Haiku 4.5This pageResults on 10 of 12 axes$1 / $597 tokens/sFirst token in 19 s
Prices and speeds read between Oct 26, 2026 and Oct 28, 2026.
Claude Haiku 4.5 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 Haiku 4.5Not 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 Haiku 4.542.2%
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. 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 Haiku 4.566.7%Epoch AI's runBenchmark: OTIS Mock AIME 2024-2025, accuracy, high reasoning. From another source, so it is drawn and marked but not ranked with the others.Epoch AI's run with a 32K thinking budget, the highest it ran. Without extended thinking the same model scored 35.8.
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 Haiku 4.571.2%Epoch AI's run with a 32K-token thinking budget. With thinking off it scores 60.5%.
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 Haiku 4.510.4%
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 Haiku 4.53.2%Unusual next to its other results. Artificial Analysis publishes 3.2 for the reasoning version of Haiku 4.5 on this test, far below the model's other results. Artificial Analysis run of Oct 28, 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
- Claude Haiku 4.5Not yet published by Anthropic or any independent evaluator, checked Nov 2, 2026
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 Haiku 4.574.3%
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 Haiku 4.558.6%
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 Haiku 4.518%Hallucination rate 27.3% 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 Haiku 4.524.7%With extended thinking on, SpeechMap counted 39.0% of requests denied and 36.4% evaded. With it off, the model completes 20.8%.
The share of MultiChallenge's multi-turn conversations in which the model keeps every instruction it was given earlier in the conversation.
MultiChallenge, accuracy, Scale AI run
- Claude Haiku 4.550.5%On Oct 28, 2026, Scale AI ranked it 29th, with extended thinking on.Plus or minus 2.04 points (95% interval)
Cost, speed, capacity, quality and accuracy for Claude Haiku 4.5, with where each figure sits among the 41 models GILD tracks. These measures stand beside the chart and never feed it.
Speed
86tokens a second
Output speed. How fast it writes once the answer starts. Run at reasoning off.
- First token
- 0.5 s
- Whole answer
- 24 s
Capacity
200Ktokens
Context window. The most one request can hold, as the maker states it.
- Reads
- Text, Images
Quality
15.4of 100
Intelligence Index. One composite score across independent evaluations. Run at reasoning off.
- GDPval knowledge work
- 732 Elo
- Terminal-Bench 4.0
- 0.0%
- Epoch Capabilities Index
- 142
Hallucination
27.3%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 reasoning on.
- Knowledge accuracy
- 18.0%
Where you can get it
14of 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, Epoch AI, GILD's route matrix and Anthropic, read Oct 26 to Nov 1, 2026. Each measure's definition and source open under . Not yet published for Claude Haiku 4.5: Cached input and Max output.
Every value with its benchmark, run and source
| Axis | Benchmark and setting | Claude Haiku 4.5 | 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 | 42.2% | Claude 4.5 Haiku (Reasoning)Effort: reasoning on. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Math | OTIS Mock AIME 2024-2025Accuracy, OTIS Mock AIME 2024-2025, high reasoning. Epoch AI's run with a 32K thinking budget, the highest it ran. Without extended thinking the same model scored 35.8.Stands in for FrontierMath Tiers 1-3, accuracy, pass@1, highest effort run, which has no run of Claude Haiku 4.5 yet. | 66.7% | Effort: 32K thinking budget. Harness: none. | Epoch AIRun by Epoch AI | Oct 22, 2025 |
| Science | GPQA DiamondAccuracy, pass@1, highest effort run. Epoch AI's run with a 32K-token thinking budget. With thinking off it scores 60.5%. | 71.2% | Effort: 32K thinking budget. Harness: none. | Epoch AI | Oct 22, 2025 |
| Hard reasoning | Humanity's Last ExamAccuracy, text-only questions, no tools | 10.4% | Claude 4.5 Haiku (Reasoning)Effort: reasoning on. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Tool use | AutomationBench-AAScore, Artificial Analysis run. Artificial Analysis publishes 3.2 for the reasoning version of Haiku 4.5 on this test, far below the model's other results. | 3.2%Unusual next to its other results. Artificial Analysis publishes 3.2 for the reasoning version of Haiku 4.5 on this test, far below the model's other results. Artificial Analysis run of Oct 28, 2026. | Claude 4.5 Haiku (Reasoning)Effort: reasoning on. Harness: Artificial Analysis AutomationBench harness. | Artificial Analysis | Oct 28, 2026 |
| Computer use | OSWorld 2.1Partial score, full 108-task set, v2.1 release | Not yet published by Anthropic or any independent evaluator, checked Nov 2, 2026 | |||
| Long context | AA-LCR v1.1Accuracy, Artificial Analysis run | 74.3% | Claude 4.5 Haiku (Reasoning)Effort: reasoning on. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Multimodal | MMMU-ProOverall accuracy, no tools | 58.6% | Claude 4.5 Haiku (Reasoning)Effort: reasoning on. Harness: none. | Artificial Analysis | Oct 28, 2026 |
| Factuality | AA-Omniscience AccuracyAccuracy, Artificial Analysis run | 18%Hallucination rate 27.3% in the same run (lower is better) | Claude 4.5 Haiku (Reasoning)Effort: reasoning on. Harness: none. | Artificial Analysis | Oct 27, 2026 |
| Answers in full | SpeechMap% Complete over 2,120 contested requests, reasoning-on entry. With extended thinking on, SpeechMap counted 39.0% of requests denied and 36.4% evaded. With it off, the model completes 20.8%. | 24.7% | Effort: reasoning on. Harness: none. | SpeechMap.AI | Oct 27, 2026 |
| Instruction following | MultiChallengeAccuracy, Scale AI run. On Oct 28, 2026, Scale AI ranked it 29th, with extended thinking on. | 50.5%Plus or minus 2.04 points (95% interval) | Effort: reasoning on. Harness: none. | Scale AI SEAL | Oct 28, 2026 |
Price and speed
- Claude Haiku 4.5 lists at $1 per million input tokens and $5 per million output tokens. Anthropic pricing, Oct 26, 2026.
- Claude Haiku 4.5 writes 97 output tokens per second on Anthropic's API, and its first token arrives 19 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 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 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 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 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 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 Haiku 4.5 beyond the twelve chart axes, each with the run it comes from and its publisher. These stay separate measures; none is folded into the chart.
| Measure | Claude Haiku 4.5 | Run | Source | Read |
|---|---|---|---|---|
| Specs and access | ||||
| Context windowThe most tokens one request can hold, as the maker states it. Size alone says nothing about how well the model uses a long input; the Long context axis measures that. | 200K | Artificial Analysis | Oct 27, 2026 | |
| ReadsThe kinds of input the model accepts. | Text, Images | Artificial Analysis | Oct 27, 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 27, 2026 | |
| Routes offering itOf the 19 clouds, gateways and coding products GILD tracks, how many offer the release today, preview included. | 14 of 19 | GILD route matrix | Oct 28, 2026 | |
| Cost | ||||
| Answer tokens per taskLower is better. Answer tokens per Intelligence Index task, reasoning excluded. | 10,820 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, cache readsLower is better. The cache-read share of AA's cost per Intelligence Index task. | $0.04 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, cache writesLower is better. The cache-write share of AA's cost per Intelligence Index task. | $0.084 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, inputLower is better. The input-token share of AA's cost per Intelligence Index task. | $0.14 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, outputLower is better. The answer-token share of AA's cost per Intelligence Index task. | $0.092 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, reasoningLower is better. The reasoning-token share of AA's cost per Intelligence Index task. | $0.038 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Cost per taskLower is better. What one Intelligence Index task cost AA at list price, input, cache, output and reasoning tokens together. | $0.23 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Cost to run the indexLower is better. What the whole Intelligence Index run cost AA at list price. The runs cost from tens of dollars to about $13,000, so the axis is log from $10 to $100,000. | $546.96 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Output tokens per taskLower is better. Tokens the model wrote per Intelligence Index task, reasoning included: how verbose it is. | 18,485 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Reasoning tokens per taskLower is better. Reasoning tokens per Intelligence Index task. | 7,665 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Speed | ||||
| End-to-end response timeLower is better. Seconds AA measures for a whole response on its standard prompt. | 24 s | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Time to first answer tokenLower is better. Seconds until the first answer token, after any reasoning, on AA's API runs. | 18 s | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Output speedMedian output tokens per second on AA's API runs, with the 5th and 95th percentile when AA prints them. | 86 tokens/s | Claude 4.5 Haiku (Non-reasoning) | Artificial Analysis | Oct 27, 2026 |
| Time per taskLower is better. Wall-clock seconds per Intelligence Index task. Runs take from about 15 s to about 33 min, so the axis is log from 1 s to 10,000 s. | 144 s | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 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. | 0.5 s | Claude 4.5 Haiku (Non-reasoning) | Artificial Analysis | Oct 27, 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. | 27.3% | Reasoning on | Artificial Analysis | Oct 27, 2026 |
| Omniscience accuracyShare of AA-Omniscience knowledge questions answered correctly. | 18% | Reasoning on | Artificial Analysis | Oct 27, 2026 |
| Omniscience indexAA-Omniscience index: correct answers minus wrong answers, declines neutral, -100 to 100. | -4.4 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 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. | 12.6% | 32K thinking tokens | Epoch AI | Aug 27, 2026 |
| Knowledge work | ||||
| AA-BriefcaseAA-Briefcase overall Elo for long business deliverables, with AA's 95% interval. | 616 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| AnalystAgent (AA run)AA's AnalystAgent score for analyst workflows. | 15% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| GDP-PDF (AA run)Share of GDP-PDF document tasks where every check passes. | 3.8% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| GDPval-AAGDPval-AA Elo: AA's run of economically valuable knowledge-work tasks, graded pairwise, with AA's interval. | 732 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| MLCR (AA run)AA's MLCR overall score for long, multi-document reading. | 5% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Vending-Bench 2Vending-Bench 2 final balance of a simulated vending business run by the model, as Epoch AI republishes it. | $458.89 | Andon Labs (via Epoch AI) | Oct 26, 2026 | |
| Capability beyond the chart | ||||
| AA-LCRAA long-context reasoning accuracy. | 49.7% | Claude 4.5 Haiku (Non-reasoning) | Artificial Analysis | Oct 27, 2026 |
| ALE-BenchALE-Bench performance rating on long optimization contests, as Epoch AI republishes it. | 653 | 32K thinking tokens | Sakana AI (via Epoch AI) | Oct 26, 2026 |
| ARC-AGI-2ARC-AGI-2 score from the ARC Prize maintainers, as Epoch AI republishes it. | 1.3% | ARC Prize Foundation (via Epoch AI) | Oct 26, 2026 | |
| Chess puzzles (Epoch)Share of chess puzzles solved, Epoch AI's run. | 4% | 32K thinking tokens | Epoch AI | Oct 13, 2026 |
| CritPt (AA run)Share of CritPt research-level physics problems solved in AA's run. | 0% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| DTBenchDTBench accuracy, as Epoch AI republishes it. | 73.6% | Redwood Research (via Epoch AI) | Oct 26, 2026 | |
| EnterpriseOps-Gym (AA run)AA's EnterpriseOps-Gym score for enterprise operations agents. | 29.4% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Epoch Capabilities IndexEpoch Capabilities Index: Epoch AI's composite across its benchmark hub, with its confidence interval. | 142 | Claude Haiku 4.5 | Epoch AI | Oct 26, 2026 |
| GPQA Diamond (AA run)GPQA Diamond accuracy in AA's run. | 64.6% | Claude 4.5 Haiku (Non-reasoning) | Artificial Analysis | Oct 27, 2026 |
| GPQA Diamond (Epoch)GPQA Diamond accuracy, best scorer, Epoch AI's run. | 71.2% | 32K thinking tokens | Epoch AI | Oct 22, 2025 |
| Humanity's Last Exam (AA run)Share of Humanity's Last Exam questions answered correctly in AA's run. | 4.2% | Claude 4.5 Haiku (Non-reasoning) | Artificial Analysis | Oct 27, 2026 |
| IFBench (AA run)Instruction-following accuracy on IFBench in AA's run. | 54.3% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Intelligence IndexArtificial Analysis Intelligence Index: AA's composite of its own evaluation runs, 0 to 100 points. | 15.4 | Claude 4.5 Haiku (Non-reasoning) | Artificial Analysis | Oct 27, 2026 |
| IT-Bench SRE (AA run)AA's IT-Bench SRE score for incident and reliability agents. | 27.3% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 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. | 30.9 | Redwood Research (via Epoch AI) | Oct 26, 2026 | |
| MMMU-Pro (AA run)Multimodal understanding accuracy on MMMU-Pro in AA's run. | 58.6% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| OTIS Mock AIME (Epoch)Share of OTIS Mock AIME 2024 to 2025 problems solved, Epoch AI's run. | 66.7% | 32K thinking tokens | Epoch AI | Oct 22, 2025 |
| SciCode (AA run)SciCode subproblem accuracy in AA's run. | 42.2% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| tau-Banking (AA run)AA's tau-Banking tool-use score. | 9.3% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| tau2-Bench (AA run)AA's tau2-Bench tool-use score. | 54.7% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Terminal-Bench 4.0 (AA run)Share of Terminal-Bench 4.0 tasks solved in AA's own harness. | 0% | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| WebDev ArenaWebDev Arena score from human pairwise votes on web builds, with its 95% interval, as Epoch AI republishes it. | 1,329 | LMArena (via Epoch AI) | Oct 26, 2026 | |
| Domains | ||||
| EconomicsArtificial Analysis capability score for economics questions, 0 to 100 points. | 26.4 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| EngineeringArtificial Analysis capability score for engineering questions, 0 to 100 points. | 19.5 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Finance and accountingArtificial Analysis capability score for finance and accounting questions, 0 to 100 points. | 14.7 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Healthcare and medicalArtificial Analysis capability score for healthcare and medical questions, 0 to 100 points. | 15.5 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| LegalArtificial Analysis capability score for legal questions, 0 to 100 points. | 18.9 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
| Strategy and operationsArtificial Analysis capability score for strategy and operations questions, 0 to 100 points. | 10.1 | Claude 4.5 Haiku (Reasoning) | Artificial Analysis | Oct 27, 2026 |
Routes, prices and uptime
Where Claude Haiku 4.5 is offered, what each route charges, and how each endpoint is holding up.
Where it is offered
14 of 19 routes GILD tracks offer Claude Haiku 4.5 today, preview included. Read Oct 28, 2026 from each route's own pages.
| Route | Status | Model ID | Limits and lifecycle | Sources |
|---|---|---|---|---|
| Amazon Bedrock | Available | us./eu./au./jp./in./global.anthropic.claude-haiku-4-5-20251001-v1:0 (bedrock-runtime)anthropic.claude-haiku-4-5 (bedrock-mantle) | AWS's model card, read Oct 28, 2026: bedrock-runtime takes a geo (us., eu., au., jp., in.) or global inference profile ID, and the bare model ID isn't supported for on-demand throughput. Geo and global profiles can route requests outside the source Region; for single-Region inference, AWS points to bedrock-mantle with the bare ID anthropic.claude-haiku-4-5. 200K context, 64K max output. | Amazon Web Services, Claude Haiku 4.5 |
| Claude Code | Available | claude-haiku-4-5-20251001 | By full model name on the Anthropic API, or provider ARN, version or deployment name; aliases resolve per provider; the haiku alias resolves to Haiku 4.5 on Claude Platform on AWS, Amazon Bedrock, Google Cloud's Agent Platform and Microsoft Foundry (page read Oct 28, 2026) | Anthropic |
| Claude on Google Cloud (Anthropic managed) | Available | claude-haiku-4-5-20251001 | Claude API model IDs (dated IDs use a hyphen) | Anthropic, Claude Haiku 4.5Anthropic, Claude Models on Google Cloud (Anthropic managed) |
| Claude Platform on AWS | Available | claude-haiku-4-5 | Same ID as the Claude API | Anthropic |
| Cursor | Available | available, hidden by default; Premium plan or higher, API list price | Anysphere (Cursor) | |
| Databricks | Available | databricks-claude-haiku-4-5 | available | Databricks, Databricks-hosted inferenceDatabricks, Detailed list of models supported by Databricks Foundation Model APIs |
| The maker's own API | Available | claude-haiku-4-5-20251001 (alias claude-haiku-4-5) | context / max output 200K / 64K; status per deprecations table | Anthropic, Claude Haiku 4.5Anthropic, Model deprecations |
| GitHub Copilot | Available | not statedpicker label Claude Haiku 4.5 | available (GA) | GitHub |
| GitHub Models | Retired | not applicableservice retired | service retired July 30, 2026 | GitHub, GitHub Models |
| Google Cloud Vertex / Agent Platform (Google managed) | Available | claude-haiku-4-5 (GAversion @20251001) | retirement not sooner than Dec 7, 2026; input / output 200,000 / 64,000 | Google, Anthropic's Claude on Google Cloud modelsGoogle, Anthropic's Claude Haiku 4.5 on Google CloudAnthropic |
| Microsoft Foundry | Available | claude-haiku-4-5 | deployment name defaults to model ID; hosted on Azure and Anthropic; context 200K; no Message Batches API | AnthropicMicrosoft Learn |
| OpenCode | Available | claude-haiku-4-5 | OpenCode Zen gateway, Anthropic Messages endpoint | Anomaly (OpenCode), ModelsOpenCode (Anomaly) |
| OpenRouter | Available | anthropic/claude-haiku-4.5 | context / max completion 200,000 / 64,000 | OpenRouter |
| Snowflake Cortex | Available | claude-haiku-4-5 | Regions: Cross Cloud (Any Region); AWS US (Cross-Region); AWS US Commercial Gov (Cross-Region); AWS EU (Cross-Region); AWS APJ (Cross-Region); AWS JP (Cross-Region); AWS AU (Cross-Region). Context 200,000; maximum output 64,000 tokens. | Snowflake |
| Windsurf / Devin | Available | MODEL_PRIVATE_11 | 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 $1 / $5 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 | $1 / $5 | Anthropic, Oct 26, 2026 | ||
| Artificial Analysis price record | $1 / $5 | $0.1 | Blended $2, 3 input : 1 output, no cacheBlended $0.77, 7 cache-hit : 2 input : 1 outputCache write $1.25 | Artificial Analysis, Oct 27, 2026 |
Lineup
Anthropic's 14 releases in 4 families, oldest to newest along each tier, with list price and speed. Claude Haiku 4.5 is lit.
CurrentLegacyThis model
Price is the list price per 1M tokens, input / output. Speed is median output tokens per second. Bars share one scale across the lineup. Read between Oct 26, 2026 and Oct 28, 2026.
Claude Haiku
Anthropic's small, fast Claude model family for high-volume, latency-sensitive work.
2 releases
- This page4.5Legacy. In 4 products we coverPrice$1 / $5Speed97 tok/s
- 5.5Current. In 6 products we coverPrice$0.10 / $0.50Speed240.7 tok/s
Claude Sonnet
Anthropic's balanced Claude model family.
4 releases
Claude Opus
Anthropic's high-capability Claude model family.
6 releases
- 4.5Legacy. In 4 products we coverPrice$5 / $25Speed58.8 tok/s
- 4.6Legacy. In 4 products we coverPrice$5 / $25Speed47.7 tok/s
- 4.7Legacy. In 4 products we coverPrice$5 / $25Speed54.7 tok/s
- 4.8Legacy. In 4 products we coverPrice$5 / $25Speed65.9 tok/s
- 5Legacy. In 4 products we coverPrice$5 / $25Speed53.3 tok/s
- 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 Haiku 4.5 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 Haiku 4.5, 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 Haiku 4.5
- Amazon Bedrock vs Microsoft Foundry: Which Cloud AI Platform Fits Your Stack?Compares routes that serve Claude Haiku 4.5
- Claude API vs Gemini API: Which Model Platform Fits Your Workloads?Compares routes that serve Claude Haiku 4.5
- Claude API vs OpenAI API: Top Scores or Lower Cost per Task?Compares routes that serve Claude Haiku 4.5
- DeepSeek API vs Claude API: Price per Task or Controls and Residency?Compares routes that serve Claude Haiku 4.5
- DeepSeek API vs OpenRouter: Buy DeepSeek From DeepSeek, or From Another Host?Compares routes that serve Claude Haiku 4.5
- Gemini API vs Amazon Bedrock: One Model Family or a Model Marketplace?Compares routes that serve Claude Haiku 4.5
- Gemini API vs Gemini Enterprise Agent Platform: Which Route to Gemini?Compares routes that serve Claude Haiku 4.5
- Gemini Enterprise Agent Platform vs Microsoft Foundry: Google Cloud or Azure for Models and AgentsCompares routes that serve Claude Haiku 4.5
- LiteLLM vs OpenRouter: Run Your Own Gateway or Rent One?Compares routes that serve Claude Haiku 4.5
- OpenRouter vs Portkey: Rent Model Access or Run a Governed Gateway?Compares routes that serve Claude Haiku 4.5
- Together AI vs OpenRouter: One Open-Model Host or a Router Across HostsCompares routes that serve Claude Haiku 4.5
What practitioners report
Strongest on Speed, weakest on Reliability.
Each figure is the share of accounts naming Claude Haiku 4.5 that speak well of it on that axis. An axis is scored once praise and concerns are both on record from at least five accounts by three authors. An account from the maker, a company that sells or serves the model, or the maker's expert program is listed and counts toward no figure.
| Axis | Favorable | Accounts |
|---|---|---|
| Quality and reasoningWhether its answers and code are right on the author's own task: reasoning, accuracy, instruction following, and consistency. | 58% | 14 favorable, 10 not, 24 authors |
| Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track. | 43% | 3 favorable, 4 not, 6 authors |
| Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs. | 40% | 2 favorable, 3 not, 5 authors |
| Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers. | Needs 5 accounts from 3 authors | 2 favorable, 2 not, 4 authors |
| CostWhat the work costs: price per task, token use, and what caching and batch save. | 29% | 4 favorable, 10 not, 12 authors |
| SpeedResponse time, time to first token, and throughput. | 78% | 7 favorable, 2 not, 9 authors |
| ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked. | 29% | 2 favorable, 5 not, 7 authors |
Every model on these seven axes
| Axis | Claude Haiku 4.5 | 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 Opus 4.7 | Claude Sonnet 4.6 | Claude Opus 4.6 | Claude Opus 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 | 58%14 favorable, 10 not, 24 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 | 57%12 favorable, 9 not, 21 authors | 67%12 favorable, 6 not, 18 authors | 70%19 favorable, 8 not, 27 authors | 62%13 favorable, 8 not, 20 authors | 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 | 43%3 favorable, 4 not, 6 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 | 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 | 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 | 40%2 favorable, 3 not, 5 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 | 50%4 favorable, 4 not, 7 authors | 71%5 favorable, 2 not, 7 authors | 64%7 favorable, 4 not, 11 authors | 40%4 favorable, 6 not, 10 authors | 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 | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 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 | 29%4 favorable, 10 not, 14 authors | 57%4 favorable, 3 not, 7 authors | 45%5 favorable, 6 not, 11 authors | 67%8 favorable, 4 not, 12 authors | 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 | 29%4 favorable, 10 not, 12 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%7 favorable, 7 not, 13 authors | 50%6 favorable, 6 not, 12 authors | 33%7 favorable, 14 not, 20 authors | 53%8 favorable, 7 not, 15 authors | 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 | 78%7 favorable, 2 not, 9 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 | 63%5 favorable, 3 not, 8 authors | 17%1 favorable, 5 not, 6 authors | 36%4 favorable, 7 not, 11 authors | 73%8 favorable, 3 not, 11 authors | 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 | 29%2 favorable, 5 not, 7 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 | 18%2 favorable, 9 not, 11 authors | 17%1 favorable, 5 not, 6 authors | 20%3 favorable, 12 not, 15 authors | 38%6 favorable, 10 not, 16 authors | 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 54 accounts behind Claude Haiku 4.5's figures
GILD searched Hacker News, GitHub, Reddit, X, Artificial Analysis, OpenRouter and the web for accounts that name Claude Haiku 4.5.
Quality and reasoning 58%
- Favorable
cupeled with encouraging initial output quality and efficient ingestion of repos
Comment on: Claude Haiku 4.5. Topfi, Hacker News commenter, self-described, Oct 16, 2025. Haiku 4.5 with and without reasoning, on code repositories.
- Favorable
have indeed shown very convincing results on specific, scoped tasks
Comment on HN thread. axi0m, Hacker News commenter, self-described, Jun 2, 2026. Haiku 4.5 on scoped tasks generated by Opus 4.6, in production.
- Favorable
At work we use haiku 4.5 for a handful of latency sensitive tasks that are fairly simple. It performs well.
Comment on: Claude Haiku 5.5. d1l, Hacker News commenter, self-described, Oct 7, 2026. Haiku 4.5 at work for latency-sensitive tasks, against Haiku 5.5.
- Favorable
Both evals and Human pairwise tests for our use case are giving Haiku 4.5 first place in pretty much all tests
Comment on: Claude Haiku 5.5. HyperL0gi, Hacker News commenter, self-described, Oct 7, 2026. Haiku 4.5 against Haiku 5.5 in the commenter's evals.
- Unfavorable
9x cheaper than Haiku 4.5 and 2 letter grades better
Comment on: Claude Haiku 5.5. chriddyp, Hacker News commenter, self-described, Oct 7, 2026. Haiku 4.5 against Haiku 5.5 on Plotly's DataAnalyticsBench.
- Unfavorable
The remaining nine models fall below 65%, with a long tail down to Claude Haiku 4.5 at 40.2%.
MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers. Chaithanya Bandi and coauthors, Scale AI and National University of Singapore, self-described, May 19, 2026. Claude Haiku 4.5 among 20 models on MCP-Atlas.
- Favorable
The cheapest Claude model outperformed the mid-tier Claude model on the same context.
You're Probably Using the Wrong Bedrock Model. Here's How to Tell.. Brian Carpio, Founder and CEO of OutcomeOps, Apr 1, 2026. Haiku 4.5 on Amazon Bedrock in a RAG sales assistant, against Sonnet 4.6 and six other models.
- Favorable
It has near perfect accuracy.
Comment on: Claude Haiku 5.5. enraged_camel, Hacker News commenter, self-described, Oct 7, 2026. Haiku 4.5 turning natural-language requests into structured specs.
- Favorable
with gpt-5-mini and now Haiku 4.5, I'd phrase the question the other way around: what do you need the big models for anymore?
Comment on: Claude Haiku 4.5. pietz, Hacker News commenter, self-described, Oct 15, 2025. Haiku 4.5 and gpt-5-mini for user-facing workflows.
- Unfavorable
Gpt-5-mini was much slower, but cheaper and better at generating good tags. Claude-haiku-4.5 was not far behind
Comment on: Show HN: What Is Hacker News Working On?. fumeux_fume, Hacker News commenter, self-described, Nov 10, 2025. claude-haiku-4.5 generating tags, against gpt-5-mini.
- Favorable
haiku 4.5 is good enough for fanout
Comment on: Measuring Claude 4.7's tokenizer costs. memcoder, Hacker News commenter, self-described, Apr 18, 2026. Haiku 4.5 for about 70% of implementation in a tiered Claude pipeline.
- Favorable
Haiku 4.5 scores 20/25, and Haiku is certainly better than Sonnet 3.6
Comment on: Running local models on an M4 with 24GB memory. nl, Hacker News commenter, self-described, May 11, 2026. Haiku 4.5 on the commenter's SQL benchmark.
- Unfavorable
Unfortunately there's no defending Haiku 4.5 at this point when cheaper and better options are available
Comment on: MAI-Code-1-Flash. bel8, Hacker News commenter, self-described, Jun 3, 2026. Haiku 4.5 via GitHub Copilot, against cheaper models on Artificial Analysis.
- Unfavorable
Haiku is not competitive, Deepseek v4 flash outperforms my uses for about $0.10 / $0.20
Comment on: Anthropic's model naming, extrapolated. mchusma, Hacker News commenter, self-described, Jun 10, 2026. Haiku 4.5 at $1/$5 against DeepSeek v4 flash.
- Favorable
when Sonnet 4.6 and Haiku 4.5 didn't break a sweat
Comment on: GLM 5.2 Is Out. zschallz, Hacker News commenter, self-described, Jun 13, 2026. Sonnet 4.6 and Haiku 4.5 on full-stack coding, against GLM.
- Favorable
I am using a Claude Q3 2024 model mostly (Haiku 4.5) at present, and it delivers what I need.
Comment on: Asian AI startups launch Mythos-like models. khurs, Hacker News commenter, self-described, Jun 28, 2026. Haiku 4.5 as the commenter's main model.
- Unfavorable
Haiku 4.5, on the other hand, is comparable to performance to Gemma4 31B
Comment on: Advancing the price-performance frontier with GPT-5.6. dannyw, Hacker News commenter, self-described, Jul 30, 2026. Haiku 4.5 against GPT-5.6 Luna and Gemma4 31B.
- Unfavorable
Haiku 4.5 is terrible for coding.
Comment on: Small Models Have Arrived. samspot, Hacker News commenter, self-described, Aug 28, 2026. Haiku 4.5 for coding at work, against Luna.
- Unfavorable
In particular Haiku 4.5 is rubbish
Comment on: Our decision on Cursor following its acquisition by SpaceX. ifwinterco, Hacker News commenter, self-described, Aug 29, 2026. Haiku 4.5 in Claude Code.
- Unfavorable
The task fails, while the same task passes with Claude Code's default model.
Haiku 4.5 in a long analysis: runs each cell alone, never looks at plots, leaves an error. jowch, GitHub user and EndeavorMCP maintainer, self-described, Oct 22, 2026. claude-haiku-4-5 in Claude Code 2.1.308 on a long notebook analysis task.
- Unfavorable
failed several steps that `claude-sonnet-5` and `claude-opus-4-8` passed with identical inputs
Haiku 4.5 skips Scan records and required Pursuit outputs in host smoke. zhenglimindesign-ing, GitHub user, self-described, Oct 7, 2026. Haiku 4.5 (claude-haiku-4-5-20251001) in headless Claude Code 2.1.218.
- Unfavorable
Claude 4.5 Haiku (Non-reasoning) is below average in intelligence
Claude 4.5 Haiku (Non-reasoning) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking, self-described, Oct 26, 2026. Claude Haiku 4.5 (Claude 4.5 Haiku, non-reasoning) on the Artificial Analysis Intelligence Index.
- Unfavorable
Claude 4.5 Haiku (Reasoning) is among the least intelligent models
Claude 4.5 Haiku (Reasoning) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking, self-described, Oct 26, 2026. Claude Haiku 4.5 (Claude 4.5 Haiku, reasoning) on the Artificial Analysis Intelligence Index.
- Favorable
Haiku excels at execution when you know what needs to be done.
Launching an Army of Haiku 4.5 Agents. dcodes, DevRel at Shuttle, self-described, Oct 23, 2025. Haiku 4.5 task-worker and Explore subagents in Claude Code, orchestrated by Sonnet 4.5, on the Shuttle CLI.
- Favorable
In our internal tests, Haiku 4.5 came close to Sonnet 4.5 in terms of quality
Augment Code on X: Haiku 4.5 advances small-model performance significantly. Augment Code, makers of the Augment coding agent, self-described, Oct 15, 2025. Haiku 4.5 in Augment Code's internal tests against Sonnet 4.5.
- Favorable
I actually got better quality output from sending it to Haiku 4.5 instead
Comment on: Mistral AI Releases Forge. SyneRyder, Hacker News commenter, self-described, Mar 18, 2026. Haiku 4.5 converting a multi-page PDF, against Mistral OCR 3.
- Unfavorable
It sucked at drawing pelicans
Claude Haiku 5.5. Simon Willison, maintainer of the llm-anthropic plugin, self-described, Oct 7, 2026. Claude Haiku 4.5, looking back from the Haiku 5.5 launch.
Tool use and structured output 43%
- Unfavorable
the lack of structured output so I hope they'll add it to Haiku 4.5 soon
Comment on: Structured outputs on the Claude Developer Platform. adidoit, Hacker News commenter, self-described, Nov 14, 2025. Haiku 4.5 at Socratify.
- Unfavorable
Native structured output: the map always comes back empty, with no error or warning.
ChatBedrockConverse json_schema structured output silently returns empty dicts for dict[str, X] fields. mr0b0t0, GitHub user, self-described, Sep 23, 2026. Claude Haiku 4.5 on Bedrock, eu-central-1, eu.anthropic.claude-haiku-4-5-20251001-v1:0.
- Unfavorable
suggesting that their default tool-use policies are poorly calibrated for MCP with unknown tools and realistic distractors
MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers. Chaithanya Bandi and coauthors, Scale AI and National University of Singapore, self-described, May 19, 2026. Claude Haiku 4.5 among 20 models on MCP-Atlas.
- Favorable
We use Haiku 4.5 to turn users' natural language queries and requests into fairly complex structured specs
Comment on: Claude Haiku 5.5. enraged_camel, Hacker News commenter, self-described, Oct 7, 2026. Haiku 4.5 turning natural-language requests into structured specs.
- Favorable
It continues to be absurdly capable for converting natural language to structured JSON based on a set of fairly complex business rules.
Comment on: Claude Opus 5.5. enraged_camel, Hacker News commenter, self-described, Sep 22, 2026. Haiku 4.5 inside the commenter's product, natural language to JSON.
- Unfavorable
That is 36 `read_cell` calls, each sending back the code it had just written.
Haiku 4.5 in a long analysis: runs each cell alone, never looks at plots, leaves an error. jowch, GitHub user and EndeavorMCP maintainer, self-described, Oct 22, 2026. claude-haiku-4-5 in Claude Code 2.1.308 on a long notebook analysis task.
- Unfavorable
`scan_state.py` was never called, so no Scan run or observation was saved.
Haiku 4.5 skips Scan records and required Pursuit outputs in host smoke. zhenglimindesign-ing, GitHub user, self-described, Oct 7, 2026. Haiku 4.5 (claude-haiku-4-5-20251001) in headless Claude Code 2.1.218.
- Favorable
Haiku 4.5 delivers near-frontier coding quality with low latency and consistent tool reliability.
Claude Haiku 4.5 is now available in Augment Code. Augment Code, makers of the Augment coding agent, self-described, Oct 15, 2025. Claude Haiku 4.5 in Augment Code.
Long context 40%
- Unfavorable
Course with 200k being a hard limit, that is a clear downside compared to GPT-5
Comment on: Claude Haiku 4.5. Topfi, Hacker News commenter, self-described, Oct 16, 2025. Haiku 4.5 with and without reasoning, on code repositories.
- Favorable
The sub agent reads a whole bunch of logs and returns only the relevant parts to the parent agent.
Comment on: We gave terabytes of CI logs to an LLM. aluzzardi (Andrea Luzzardi), co-founder and CTO of Mendral, Feb 27, 2026. haiku 4.5 subagents for log research, dispatched by Opus 4.6.
- Unfavorable
Haiku 4.5 in a long analysis: runs each cell alone, never looks at plots, leaves an error
Haiku 4.5 in a long analysis: runs each cell alone, never looks at plots, leaves an error. jowch, GitHub user and EndeavorMCP maintainer, self-described, Oct 22, 2026. claude-haiku-4-5 in Claude Code 2.1.308 on a long notebook analysis task.
- Favorable
Haiku 4.5 detected some footers that were on every page and moved them to be the footer at the end of the entire document instead
Comment on: Mistral AI Releases Forge. SyneRyder, Hacker News commenter, self-described, Mar 18, 2026. Haiku 4.5 converting a multi-page PDF, against Mistral OCR 3.
- Unfavorable
No 1m for Haiku (this new model) and Opus. This means 2.5 Flash or Grok 4 fast takes all the low end business for large context needs.
Comment on: Claude Haiku 4.5. leetharris, Hacker News commenter, self-described, Oct 15, 2025. Claude Haiku 4.5 at launch, 200k context without the 1M option.
Developer experience Needs 5 accounts from 3 authors
- Unfavorable
I tell it not to modify the contents, but it's haiku, so sometimes it just does it anyway
Comment on: You should write an agent. richardlblair, Hacker News commenter, self-described, Nov 10, 2025. Haiku 4.5 cleaning up Whisper transcripts.
- Favorable
I have had the best overall results with Haiku 4.5, simply because GPT-5.4-nano is still unwilling to play nice with my approach to UI components
Comment on: Introspective Diffusion Language Models. Topfi, Hacker News commenter, self-described, Apr 14, 2026. Haiku 4.5 generating UI from pre-made components, against GPT-5.4-nano and Mercury 2.
- Favorable
Haiku 4.5 still has a small bit of that charm
Comment on: Gemini 3.8 Live and 3.8 Live Extended Thinking. FranzFerdiNaN, Hacker News commenter, self-described, Sep 16, 2026. Haiku 4.5 and Sonnet 4.5 for non-coding writing.
- Unfavorable
Execution failed: Error: Reasoning effort 'medium' is not supported for model 'claude-haiku-4.5'.
Reasoning effort 'medium' is not supported for model 'claude-haiku-4.5'. indeherb, GitHub user, self-described, Aug 3, 2026. claude-haiku-4.5 as the explore and task sub-agent in GitHub Copilot CLI 1.0.77.
- Favorable
It's also faster than average and fairly concise.
Claude 4.5 Haiku (Reasoning) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking, self-described, Oct 26, 2026. Claude Haiku 4.5 (Claude 4.5 Haiku, reasoning) on the Artificial Analysis Intelligence Index.
Cost 29%
- Favorable
I have seen Haiku 4.5 be far better in using what I'd consider a justifiable amount of input tokens over e.g. GPT-5 models
Comment on: Claude Haiku 4.5. Topfi, Hacker News commenter, self-described, Oct 16, 2025. Haiku 4.5 with and without reasoning, on code repositories.
- Favorable
Haiku excels here. Fast, cheap, thorough.
You're Probably Using the Wrong Bedrock Model. Here's How to Tell.. Brian Carpio, Founder and CEO of OutcomeOps, Apr 1, 2026. Haiku 4.5 on Amazon Bedrock in a RAG sales assistant, against Sonnet 4.6 and six other models.
- Unfavorable
I called out Claude Haiku 4.5 as being more expensive than previous Haiku models
Comment on: Claude Skills are awesome, maybe a bigger deal than MCP. simonw, Hacker News commenter, self-described, Oct 18, 2025. Claude Haiku 4.5 pricing against GPT-5 Mini, Nano and Gemini Flash Lite.
- Unfavorable
but much more expensive
Comment on: Show HN: What Is Hacker News Working On?. fumeux_fume, Hacker News commenter, self-described, Nov 10, 2025. claude-haiku-4.5 generating tags, against gpt-5-mini.
- Favorable
dispatching "log research" jobs to sub agents (haiku 4.5 which is fast/cheap)
Comment on: We gave terabytes of CI logs to an LLM. aluzzardi (Andrea Luzzardi), co-founder and CTO of Mendral, Feb 27, 2026. haiku 4.5 subagents for log research, dispatched by Opus 4.6.
- Unfavorable
More expensive but much more reliable
Comment on: GPT-5.4 Mini and Nano. HugoDias, Hacker News commenter, self-described, Mar 17, 2026. haiku-4.5 after migrating from a model whose performance dropped.
- Unfavorable
Whereas Haiku 4.5 is $1/$5
Comment on: Anthropic's model naming, extrapolated. mchusma, Hacker News commenter, self-described, Jun 10, 2026. Haiku 4.5 at $1/$5 against DeepSeek v4 flash.
- Unfavorable
Luna is better and cheaper than the Haiku and Sonnet models I've been spending most of my time with
Comment on: Small Models Have Arrived. samspot, Hacker News commenter, self-described, Aug 28, 2026. Haiku 4.5 for coding at work, against Luna.
- Unfavorable
Haiku 4.5 has been too expensive compared to its performance for months now
Comment on: Claude Haiku 5.5. wyrdcurt, Hacker News commenter, self-described, Oct 7, 2026. Haiku 4.5 against Haiku 5.5 and Luna.
- Unfavorable
the same uncached input would cost around $100 with Claude Haiku 4.5
Comment on: Show HN: Made a Taboo-style game where Jev tries to guess your word. rohanm93, Hacker News commenter, self-described, Oct 3, 2026. Claude Haiku 4.5 uncached input cost, against Jev.
- Favorable
but well priced when comparing to other non-reasoning models of similar price
Claude 4.5 Haiku (Non-reasoning) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking, self-described, Oct 26, 2026. Claude Haiku 4.5 (Claude 4.5 Haiku, non-reasoning) on the Artificial Analysis Intelligence Index.
- Favorable
but well priced when comparing to other models of similar price
Claude 4.5 Haiku (Reasoning) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking, self-described, Oct 26, 2026. Claude Haiku 4.5 (Claude 4.5 Haiku, reasoning) on the Artificial Analysis Intelligence Index.
- Unfavorable
slightly more expensive than Haiku 3.5 ($0.80/$4) and a lot more expensive than the original Claude 3 Haiku
Introducing Claude Haiku 4.5. Simon Willison, creator of Datasette and the LLM tool, self-described, Oct 15, 2025. Claude Haiku 4.5 through llm-anthropic 0.20.
- Favorable
haiku 4.5 (also pretty good for a price)
Comment on: Gemini 3.1 Pro. attentive, Hacker News commenter, self-described, Feb 19, 2026. haiku 4.5 as a coder in opencode, against Gemini Flash 3.0 and Sonnet.
- Unfavorable
so the cost of Haiku on the same tasks tends to only be about double
Comment on: MAI-Code-1-Flash. easygenes, Hacker News commenter, self-described, Jun 3, 2026. Claude Haiku 4.5 reasoning mode against Qwen3.6-35B-A3B on Artificial Analysis metrics.
- Unfavorable
relatively expensive even back then, and a full 10x the price of OpenAI's GPT-6 Luna
Claude Haiku 5.5. Simon Willison, maintainer of the llm-anthropic plugin, self-described, Oct 7, 2026. Claude Haiku 4.5, looking back from the Haiku 5.5 launch.
Speed 78%
- Unfavorable
Haiku 4.5 is very good but still seems to be adding a second of latency
Comment on: Claude Haiku 4.5. ilaksh, Hacker News commenter, self-described, Oct 15, 2025. Haiku 4.5 for voice and phone agents.
- Favorable
Haiku 4.5, if they can continue to offer it at such speeds with such low latency and at this price
Comment on: Claude Haiku 4.5. Topfi, Hacker News commenter, self-described, Oct 16, 2025. Haiku 4.5 with and without reasoning, on code repositories.
- Favorable
Claude Haiku 4.5 at the fast-but-inaccurate end (27s, 40.2%)
MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers. Chaithanya Bandi and coauthors, Scale AI and National University of Singapore, self-described, May 19, 2026. Claude Haiku 4.5 among 20 models on MCP-Atlas.
- Favorable
Claude Haiku 4.5 delivered its first token in 597 milliseconds on a medium-length prompt. GPT-4.1 Mini took roughly 4x longer on the identical test.
5 LLM APIs Tested for Latency: Real Data [2026]. Kunal Ganglani, Senior Staff Software Engineer, Mar 7, 2026. Claude Haiku 4.5 streaming, from a Toronto server.
- Favorable
was much faster due to the absence of thinking tokens
Comment on: Show HN: What Is Hacker News Working On?. fumeux_fume, Hacker News commenter, self-described, Nov 10, 2025. claude-haiku-4.5 generating tags, against gpt-5-mini.
- Favorable
If these numbers hold we're really looking at an almost 3x improvement in throughput and less then half the initial latency
Comment on: Claude Haiku 4.5. rbitar, Hacker News commenter, self-described, Oct 16, 2025. Claude Haiku 4.5 on OpenRouter, against Sonnet 4.
- Favorable
I'm using Claude Haiku 4.5 for my voice assistant right now and it's pretty fast
Comment on: Show HN: Forge, guardrails for an 8B model on agentic tasks. jamesponddotco, Hacker News commenter, self-described, May 19, 2026. Claude Haiku 4.5 for a Home Assistant voice assistant.
- Favorable
At 85 tokens per second, Claude 4.5 Haiku (Non-reasoning) is faster than average (81).
Claude 4.5 Haiku (Non-reasoning) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking, self-described, Oct 26, 2026. Claude Haiku 4.5 (Claude 4.5 Haiku, non-reasoning) on the Artificial Analysis Intelligence Index.
- Favorable
At 95 tokens per second, Claude 4.5 Haiku (Reasoning) is faster than average (83).
Claude 4.5 Haiku (Reasoning) - Intelligence, Performance & Price Analysis. Artificial Analysis, independent model benchmarking, self-described, Oct 26, 2026. Claude Haiku 4.5 (Claude 4.5 Haiku, reasoning) on the Artificial Analysis Intelligence Index.
- Favorable
This is another great use of the Haiku model - it's fast and efficient for codebase exploration.
Launching an Army of Haiku 4.5 Agents. dcodes, DevRel at Shuttle, self-described, Oct 23, 2025. Haiku 4.5 task-worker and Explore subagents in Claude Code, orchestrated by Sonnet 4.5, on the Shuttle CLI.
- Favorable
Haiku 4.5 achieved faster time-to-success in 85% of evaluations, completing tasks 34% faster on average.
Augment Code on X: Haiku 4.5 advances small-model performance significantly. Augment Code, makers of the Augment coding agent, self-described, Oct 15, 2025. Haiku 4.5 in Augment Code's internal tests against Sonnet 4.5.
- Unfavorable
Claude Haiku 4.5 37.1 $620 (slower) → Qwen wins all three.
Comment on: MAI-Code-1-Flash. easygenes, Hacker News commenter, self-described, Jun 3, 2026. Claude Haiku 4.5 reasoning mode against Qwen3.6-35B-A3B on Artificial Analysis metrics.
Reliability 29%
- Unfavorable
CloudWatch's AWS/Bedrock namespace showed a 14% throttle rate on Haiku and 16% on Opus over the 14 days preceding the case.
16 days, 4 channels, no AWS Bedrock quota fix. Ziva.sh, a Godot AI tool company, self-described, May 16, 2026. Claude Haiku 4.5 on Bedrock via global cross-region inference, us-west-2.
- Favorable
that forced us to migrate to haiku-4.5. More expensive but much more reliable (when anthropic up, of course)
Comment on: GPT-5.4 Mini and Nano. HugoDias, Hacker News commenter, self-described, Mar 17, 2026. haiku-4.5 after migrating from a model whose performance dropped.
- Unfavorable
The model that already worked keeps working, or the account is told beforehand that a form is needed.
friction: Bedrock asks for the Anthropic use case form after Claude Haiku 4.5 already worked. juanlo7, GitHub user, self-described, Oct 5, 2026. Claude Haiku 4.5 on Amazon Bedrock ConverseStream, us-east-1, via Strands Agents SDK 1.57.
- Unfavorable
the system quickly consumes a large number of input tokens per minute against the claude-haiku-4-5-20251001 model, triggering a 429 - rate_limit_error from the Anthropic API
[Bug]: Agent creation consumes large number of input tokens per minute on claude-haiku-4-5-20251001. joaopfg, GitHub user, self-described, Mar 16, 2026. Haiku 4.5 (claude-haiku-4-5-20251001) as Hive's default model at a 50,000 input-token-per-minute org limit.
- Favorable
You could switch your Claude Code to use Haiku and never hit rate limits.
Comment on: Qwen3.5 122B and 35B models offer Sonnet 4.5 performance on local computers. acchow, Hacker News commenter, self-described, Mar 1, 2026. Claude Haiku 4.5 in Claude Code, against Qwen3.5 35B locally.
- Unfavorable
followed by another incident involving Opus 5 and Haiku 4.5 on 19 August
Claude outage hits multiple models again. Ana Maria Constantin, writer at The Next Web, self-described, Aug 24, 2026. Haiku 4.5 in Anthropic's August 2026 incident history.
- Unfavorable
Model: Claude Haiku 4.5 Provider: anthropic Status Code: 429
Error: Claude Haiku 4.5 - 429. RayMatews, GitHub user, self-described, Feb 11, 2026. Claude Haiku 4.5 through the anthropic provider in Continue.