Cost
$5.41per task
Cost per task. One Intelligence Index task at list price, every token counted. Run at 0902.
Qwen model by Alibaba
Qwen3.8 Max
Alibaba's flagship Qwen3.8 model on Model Studio, with text, image and video input, on Alibaba Cloud Model Studio as qwen3.8-max. Since September 5, 2026 that endpoint serves the qwen3.8-max-0902 snapshot of September 2, at the same price.
Where it sits in Alibaba's lineup
- Stack role
- Foundation Model / Reasoning Engine
- Offered in
- 2 products
- Made by
- Alibaba
- Family
- Qwen, version 3.8
- Released
- Aug 2, 2026 Current
- In its family
- Release 1 of 2 in Qwen. The newest is Qwen3.8 27B.
Strengths and weaknesses
Compare with other models Up to 3 beside Qwen3.8 Max
- Qwen3.8 Max
Suggested comparisons
The models a buyer weighs against Qwen3.8 Max, picked on list price and on Artificial Analysis's Intelligence Index of overall quality. Add one to draw it beside Qwen3.8 Max.
Qwen3.8 Max
Among the 40 current releases on this chart, Qwen3.8 Max ranks 10th of 31 on Agentic coding and 8th of 24 on Multimodal. It ranks lowest on Factuality, 24th of 30 and Math, 22nd of 28. Computer use and Instruction following: not yet published by Alibaba 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.
On the chart
- Qwen3.8 MaxThis pageResults on 10 of 12 axes$2 / $640 tokens/sFirst token in 3.0 s
Prices and speeds as of Oct 29, 2026.
Qwen3.8 Max 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
- Qwen3.8 Max38.9%Vals.ai ranked the September 2 build 16th on its leaderboard of Oct 29, 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
- Qwen3.8 Max52.1%
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
- Qwen3.8 Max65.6%
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
- Qwen3.8 Max92.3%
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
- Qwen3.8 Max43.1%
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
- Qwen3.8 Max56.2%
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
- Qwen3.8 MaxNot yet published by Alibaba 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
- Qwen3.8 Max80.3%
The share of MMMU-Pro's college-level questions over charts, diagrams and photos the model answers correctly.
MMMU-Pro, overall accuracy, no tools
- Qwen3.8 Max82.8%
The share of AA-Omniscience's 6,000 knowledge questions across 42 economically relevant topics the model answers correctly from memory, without search.
AA-Omniscience Accuracy, accuracy, Artificial Analysis run
- Qwen3.8 Max29.5%Hallucination rate 27.1% 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
- Qwen3.8 Max65.3%SpeechMap tested the September 2 build with reasoning on and counted 29.8% of requests denied and 2.1% evaded.2.8% of requests failed at the provider and count against it
The share of MultiChallenge's multi-turn conversations in which the model keeps every instruction it was given earlier in the conversation.
MultiChallenge, accuracy, Scale AI run
- Qwen3.8 MaxNot yet published by Alibaba or any independent evaluator, checked Nov 2, 2026
Cost, speed, capacity, quality and accuracy for Qwen3.8 Max, with where each figure sits among the 40 models GILD tracks. These measures stand beside the chart and never feed it.
Speed
41tokens a second
Output speed. How fast it writes once the answer starts. Run at 0902.
- First token
- 2.9 s
- Whole answer
- 64 s
Capacity
984Ktokens
Context window. The most one request can hold, as the maker states it.
- Max output
- 131K
- Reads
- Text, Images
Quality
45.4of 100
Intelligence Index. One composite score across independent evaluations. Run at 0902.
- GDPval knowledge work
- 1,673 Elo
- Terminal-Bench 4.0
- 38.9%
Hallucination
27.1%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 extra-high effort.
- Knowledge accuracy
- 29.5%
Where you can get it
5of 19 routes
Routes offering it. Of the clouds, gateways and coding products GILD tracks, those offering it today.
- Open weights
- No
- Licence
- Alibaba Cloud International Website Product Terms of Service
Figures from Artificial Analysis, OpenRouter, GILD's route matrix and Alibaba Cloud, read Oct 27 to Nov 1, 2026. Each measure's definition and source open under . Not yet published for Qwen3.8 Max: Cached input and Epoch Capabilities Index.
Every value with its benchmark, run and source
| Axis | Benchmark and setting | Qwen3.8 Max | Run | Source | Date |
|---|---|---|---|---|---|
| Agentic coding | Terminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness. Vals.ai ranked the September 2 build 16th on its leaderboard of Oct 29, 2026. | 38.9% | Qwen 3.8 Max 0902Effort: not published. Harness: mini-swe-agent. Run on the Sep 2, 2026 build.Not drawn: Artificial Analysis 38.9% in another lab's harness, Oct 29, 2026. SourceNot drawn: Artificial Analysis 18.7% on an earlier build, Oct 29, 2026. SourceNot drawn: Vals.ai 34.3% on an earlier build, Oct 29, 2026. Source | Vals.ai | Oct 29, 2026 |
| Code | SciCodeSubproblem accuracy, pass@1, highest effort run | 52.1% | Qwen3.8 Max (0902)Effort: xhigh. Harness: none. Run on the Sep 2, 2026 build.Not drawn: Artificial Analysis 53.2% on an earlier build, Oct 29, 2026. Source | Artificial Analysis | Oct 29, 2026 |
| Math | FrontierMath Tiers 1-3Accuracy, pass@1, highest effort run | 65.6% | Effort: xhigh. Harness: none. Run on the Sep 2, 2026 build.Not drawn: Epoch AI 74.7% on an earlier build, Aug 4, 2026. Source | Epoch AI | Sep 2, 2026 |
| Science | GPQA DiamondAccuracy, pass@1, highest effort run | 92.3% | Effort: xhigh. Harness: none. Run on the Sep 2, 2026 build.Not drawn: Artificial Analysis 92.8% in another lab's harness, Oct 29, 2026. SourceNot drawn: Artificial Analysis 92.7% on an earlier build, Oct 29, 2026. SourceNot drawn: Epoch AI 92.7% on an earlier build, Aug 4, 2026. Source | Epoch AI | Sep 2, 2026 |
| Hard reasoning | Humanity's Last ExamAccuracy, text-only questions, no tools | 43.1% | Qwen3.8 Max (0902)Effort: xhigh. Harness: none. Run on the Sep 2, 2026 build.Not drawn: Artificial Analysis 43% on an earlier build, Oct 29, 2026. Source | Artificial Analysis | Oct 29, 2026 |
| Tool use | AutomationBench-AAScore, Artificial Analysis run | 56.2% | Qwen3.8 Max (0902)Effort: xhigh. Harness: Artificial Analysis AutomationBench harness. Run on the Sep 2, 2026 build.Not drawn: Artificial Analysis 49.2% on an earlier build, Oct 29, 2026. Source | Artificial Analysis | Oct 29, 2026 |
| Computer use | OSWorld 2.1Partial score, full 108-task set, v2.1 release | Not yet published by Alibaba or any independent evaluator, checked Nov 2, 2026 | |||
| Long context | AA-LCR v1.1Accuracy, Artificial Analysis run | 80.3% | Qwen3.8 Max (0902)Effort: xhigh. Harness: none. Run on the Sep 2, 2026 build.Not drawn: Artificial Analysis 78.3% on an earlier build, Oct 29, 2026. Source | Artificial Analysis | Oct 29, 2026 |
| Multimodal | MMMU-ProOverall accuracy, no tools | 82.8% | Qwen3.8 Max (0902)Effort: xhigh. Harness: none. Run on the Sep 2, 2026 build.Not drawn: Artificial Analysis 82.3% on an earlier build, Oct 29, 2026. SourceNot drawn: Vals.ai 88% on an earlier build, Sep 1, 2026. Source | Artificial Analysis | Oct 29, 2026 |
| Factuality | AA-Omniscience AccuracyAccuracy, Artificial Analysis run | 29.5%Hallucination rate 27.1% in the same run (lower is better) | Qwen3.8 Max (0902)Effort: xhigh. Harness: none. Run on the Sep 2, 2026 build. | Artificial Analysis | Oct 29, 2026 |
| Answers in full | SpeechMap% Complete over 2,120 contested requests, reasoning-on entry. SpeechMap tested the September 2 build with reasoning on and counted 29.8% of requests denied and 2.1% evaded. | 65.3%2.8% of requests failed at the provider and count against it | Effort: reasoning on. Harness: none. Run on the Sep 2, 2026 build.Not drawn: SpeechMap.AI 64.7% on an earlier build, Oct 29, 2026. Source | SpeechMap.AI | Oct 29, 2026 |
| Instruction following | MultiChallengeAccuracy, Scale AI run | Not yet published by Alibaba or any independent evaluator, checked Nov 2, 2026 |
Price and speed
- Qwen3.8 Max lists at $2 per million input tokens and $6 per million output tokens. Alibaba Cloud pricing, Oct 29, 2026.
- Qwen3.8 Max writes 40.3 output tokens per second on Alibaba's API, and its first token arrives 3.0 s after the request. Artificial Analysis, Oct 29, 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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 |
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| Qwen3.8 27B | 5.6%Run by Artificial AnalysisTerminal-Bench 4.0 | 46.6% | Not yet published | 90.5%Run by Artificial AnalysisGPQA Diamond | 33.9% | 48.2% | 84.3%Reported by AlibabaOSWorld-Verified | 82% | 76.3% | 17.3% | Not yet published | 79.5%Reported by AlibabaIFBench |
| ||||||||||||
| Claude Haiku 5.5 | 36.4% | 55% | 75.1% | 89.6% | 44.4% | 35.4% | 72.4%Reported by AnthropicOSWorld 2.1 | 82.7% | Not yet published | 34.7% | 78.8% | 67.7% |
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| Claude Sonnet 5.5 | 64.1% | 61% | 88.8% | 95.6% | 55% | 71.8% | 80.1%Reported by Anthropic | 82.7% | Not yet published | 51.5% | 81.6% | Not yet published |
| ||||||||||||
| Claude Opus 5.5 | 65.2% | 66.9% | 91.2% | 90.6% | 61.4% | 69.5% | 81.8%Reported by Anthropic | 84.7% | 87.7% | 65.5% | 82.8% | Not yet published |
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| Claude Fable 5.1 | 58.1% | 63.1% | 90.2% | 93.4%Run by Vals.ai | 59.1% | 59.4% | 80.7%Reported by Anthropic | 85.3% | 86.3%Run by Moonshot AI | 68.4% | 72.4% | Not yet published |
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| Claude Opus 5 | 53.5% | 56.4% | 85.6% | 93.9% | 54.9% | 56.6% | 77.7% | 79.3% | 84.7% | 60.9% | 73.7% | Not yet published |
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| Claude Sonnet 5 | 10.6% | 54.3% | 65.6% | 80.3% | 41.3% | 36.5% | 57%Reported by Anthropic | 82% | 77.3% | 40.1% | Not yet published | Not yet published |
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| Claude Fable 5 | 41.4% | 61% | 87% | 85.9% | 55.5% | 54.1% | Not yet published | 82.3% | Not yet published | 65.4% | 64.8% | 63.5%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.8 | 23.2% | 54.4% | 80% | 91% | 48.7% | 45.6% | 54.8%Run by OSWorld teamOSWorld 2.0 | 77.7% | Not yet published | 48.8% | 67.4% | 62.2%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.7 | Not yet published | 54.5% | 70.2% | 86.4% | 42.3% | Not yet published | 48.9%Run by OSWorld teamOSWorld 2.0 | 78.7% | 78.8% | 48.9% | 70.2% | 58.6%Run by Artificial AnalysisIFBench |
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| Claude Sonnet 4.6 | 3%Run by Artificial AnalysisTerminal-Bench 4.0 | 50.1% | 71.1%Run by Epoch AIOTIS Mock AIME 2024-2025 | 78.8% | 33.6% | 20.1% | 41.5%Run by OSWorld teamOSWorld 2.0 | 80% | 73.3% | 40.9% | 35.8% | 56.6%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.6 | Not yet published | Not yet published | 66% | 88.4% | 39.9% | Not yet published | Not yet published | 78% | 75.4% | 47% | 59.9% | 37.2% |
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| Claude Opus 4.5 | Not yet published | Not yet published | 34.4% | 86% | 30.1% | Not yet published | Not yet published | 77.3% | 74% | 46.6% | 57.5% | 59% |
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| Claude Haiku 4.5 | Not yet published | 42.2% | 66.7%Run by Epoch AIOTIS Mock AIME 2024-2025 | 71.2% | 10.4% | 3.2% | Not yet published | 74.3% | 58.6% | 18% | 24.7% | 50.5% |
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| Claude Sonnet 4.5 | Not yet published | 45.7% | 23.9% | 82.3% | 17.8% | 14.1% | Not yet published | 72.3% | 68.7% | 32.9% | 31.4% | 55.3% |
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| GPT-6.1 Terra | 49.5% | 55.1% | 90.9% | 94.3% | 46.2% | 60.2% | 74.2%Reported by OpenAIOSWorld 2.1 | 82.7% | 84.7% | 47.6% | Not yet published | 74.2% |
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| GPT-6.1 Sol | 55.1% | 54.2% | 93.7% | 95.4% | 52.9% | 64.9% | 78%Reported by OpenAIOSWorld 2.1 | 83% | 86% | 61.8% | 69.5% | 82% |
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| GPT-6 Luna | 13.6% | 54.6% | 78.9% | 90.5% | 38.5% | 53.2% | 48.9%Run by AnthropicOSWorld 2.1 | 83.3% | 79.7% | 39.6% | 63.4% | Not yet published |
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| GPT-6 Astra | 59.6% | 56.5% | 93.7% | 95.8% | 54.7% | 68.5% | 75.8%Run by Meta | 80.7% | 86.9% | 61.6% | 68.2% | Not yet published |
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| GPT-5.6 Sol | 37.9% | 57.1% | 89.1% | 93.5% | 49.5% | 60.1% | 62.7%Run by OSWorld teamOSWorld 2.0 | 84% | 83.4% | 69.7%Run by Epoch AISimpleQA Verified | Not yet published | 72.7%Run by Artificial AnalysisIFBench |
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| GPT-5.6 Terra | 22.7% | 55% | 86% | 93.3% | 42.9% | 59.6% | Not yet published | 83% | 80.7% | 42.3% | Not yet published | 71.2%Run by Artificial AnalysisIFBench |
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| GPT-5.6 Luna | 11.6% | 53.6% | 82.1% | 91.6% | 39.5% | 50.2% | Not yet published | 83.7% | 78.6% | 41%Run by Epoch AISimpleQA Verified | Not yet published | Not yet published |
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| GPT-5.5 | 14.6%Run by Artificial AnalysisTerminal-Bench 4.0 | 55.8% | 85.3% | 93.5%Run by Artificial Analysis | 45.8% | 47.3% | 49.5%Run by OSWorld teamOSWorld 2.0 | 84.3% | 79.9% | 63%Run by Epoch AISimpleQA Verified | Not yet published | 75.9%Run by Artificial AnalysisIFBench |
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| GPT-5.4 | Not yet published | Not yet published | 78.6% | 93.3% | 43.7% | Not yet published | Not yet published | 82% | 78.4% | Not yet published | Not yet published | 73.9%Run by Artificial AnalysisIFBench |
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| gpt-oss-120b | 14.2%Run by Terminal-Bench (via Epoch AI)Terminal-Bench 2.0 | 34% | 88.9%Run by Epoch AIOTIS Mock AIME 2024-2025 | 75.8% | 19.6% | 0.2% | Not yet published | 52% | Not yet published | 16.8%Reported by OpenAISimpleQA | 36.3% | 45.3% |
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| GPT-6 Sol | 44.4% | 57.6% | 89.8% | 94.3% | 47.9% | 61.6% | 64.4%Reported by OpenAIOSWorld 2.0 | 83.7% | 82.9% | 54.5% | 64% | Not yet published |
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| GPT-5.3-Codex | Not yet published | Not yet published | Not yet published | 91.5%Run by Artificial Analysis | 42.5% | Not yet published | Not yet published | 83.3% | 78.5% | Not yet published | Not yet published | 75.4%Run by Artificial AnalysisIFBench |
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| Gemini 4 Argon | 57.6% | 61.8% | 86% | 96.4% | 57.1% | 77.5% | 69.2%Reported by GoogleOSWorld 2.0 | 79.7% | Not yet published | 48.3% | 87% | 78.7% |
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| Gemini 3.8 Flash | 19.7% | 56.6% | 68.4% | 95.4% | 47.8% | 59.9% | 59%Reported by GoogleOSWorld 2.0 | 81.3% | 85.6% | 50.5% | 86.1% | Not yet published |
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| Gemma 4 31B | Not yet published | 45.5% | Not yet published | 85.7%Run by Artificial AnalysisGPQA Diamond | 23.6% | 4.9% | Not yet published | 69.7% | 73.4% | 10.4%Run by Epoch AISimpleQA Verified | 82.3% | 75.6%Run by Artificial AnalysisIFBench |
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| Gemini 3.1 Pro Preview | 2.5% | 58.7% | 59.6% | 94.4% | 47% | 35.4% | Not yet published | 82% | 82.4% | 54.9% | 59.9% | 71.4% |
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| Gemini 3.6 Flash | 7.1%Run by Artificial AnalysisTerminal-Bench 4.0 | 53.4% | 58.9% | 94.1% | 40.8% | 53% | 83%Reported by GoogleOSWorld-Verified | 80% | 83.2% | 66.2%Run by Epoch AISimpleQA Verified | 87.2% | Not yet published |
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| DeepSeek V4.1 Flash | 31.8% | 55.9% | 71.2% | 93.2% | 43.3% | 66.6% | 69.3%Run by Moonshot AIOSWorld 2.1 | 82.7% | 80.6% | 39.6% | Not yet published | 74.9% |
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| DeepSeek V4 Pro | 14.1% | 51% | 64.6% | 91.7% | 41% | 56.7% | Not yet published | 80.3% | Not yet published | 45.2% | 72% | Not yet published |
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| Kimi K3.1 Pro | 63.6% | 60.8% | Not yet published | 94.2%Reported by Moonshot AI | 52.5% | 73.3% | 79.6%Reported by Moonshot AIOSWorld 2.1 | 86.3% | 83.9% | 48.9% | Not yet published | Not yet published |
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| Kimi K3 | 17.2% | 59.5% | 72.2% | 93.1% | 46.9% | 58.3% | Not yet published | 88.7% | 80.5% | 50.6%Run by Epoch AISimpleQA Verified | 65.9% | Not yet published |
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| Kimi K2.7 Code | 1%Run by Artificial AnalysisTerminal-Bench 4.0 | 47.8% | 54% | 87.9% | 35% | 24.5% | Not yet published | 79.3% | Not yet published | 36.5%Run by Epoch AISimpleQA Verified | Not yet published | 63.1%Run by Artificial AnalysisIFBench |
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| Mistral Large 4 | 24.7%Run by Artificial AnalysisTerminal-Bench 4.0 | Not yet published | Not yet published | Not yet published | Not yet published | 57.8% | Not yet published | Not yet published | Not yet published | 26% | Not yet published | Not yet published |
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| Mistral Medium 3.5 | 0%Run by Artificial AnalysisTerminal-Bench 4.0 | 40.2% | Not yet published | 74.8%Run by Artificial AnalysisGPQA Diamond | 13.8% | 6.3% | Not yet published | 69.3% | 64.9% | 23% | 70.5% | 68.8%Run by Artificial AnalysisIFBench |
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| Grok 4.7 | 28.8% | 57.4% | 53% | 92.7% | 43.1% | 65.6% | Not yet published | 76.7% | Not yet published | 42.7% | 64.1% | Not yet published |
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| Grok 4.6 | 17.2% | 56.5% | 66% | 93.2% | 42.9% | 66.7% | Not yet published | 80.3% | Not yet published | 48.9%Run by Epoch AISimpleQA Verified | 83.6% | Not yet published |
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| Grok 4.5 | 8.6% | 55% | 57.2% | 93.4% | 42.7% | 57.9% | Not yet published | 79.3% | 80.4% | 48.3%Run by Epoch AISimpleQA Verified | 93.1% | Not yet published |
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| MiniMax M3.1 Flash | 25.3% | 53.4% | Not yet published | Not yet published | 48% | 72.5% | 61.7%Reported by MiniMaxOSWorld 2.0 | 79.7% | 79.1% | 45.1% | Not yet published | Not yet published |
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| Mercury 3 | 3% | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published |
| GLM-5.3-Flash | 37.4% | 51.6% | 55.8% | 90.2% | 39.9% | 60.4% | 59.1%Reported by Z.aiOSWorld 2.0 | 80% | 86%Run by Vals.aiMMMU-Pro | 28.2% | 65.4% | Not yet published |
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| GLM-5.3 | 38.9% | 59% | 68.8% | 90.9% | 42.3% | 62.2% | Not yet published | 79.7% | Not yet published | 32.3% | 71.5% | Not yet published |
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| GLM-5.2 | 1%Run by Artificial AnalysisTerminal-Bench 4.0 | 51.2% | 59.2% | Not yet published | 41.1% | 28.4% | Not yet published | 78.3% | Not yet published | 34.2%Run by Epoch AISimpleQA Verified | Not yet published | 73.3%Run by Artificial AnalysisIFBench |
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| Muse Spark Open | 6.6% | 58.4% | 69.8% | 88.6% | 43.9% | 49.7% | 80.4%Reported by MetaOSWorld-Verified | 78.3% | 80.9% | 42% | Not yet published | 74.2% |
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| Muse Wonder | 49.5% | 60.3% | 82.1% | Not yet published | 50.1% | 68.1% | 72.6%Reported by Meta | 80.7% | Not yet published | 38% | 42.7% | Not yet published |
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| Muse Spark 1.3 | 10.6% | 58.8% | 74% | 93.5%Run by Artificial AnalysisGPQA Diamond | 48.7% | 57.9% | 69.6% | 83% | 82% | 38% | 25.8% | Not yet published |
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| Llama 4 Scout | Not yet published | 21.3% | 7.8%Run by Epoch AIOTIS Mock AIME 2024-2025 | 51.8% | 3.8% | 0.2% | Not yet published | 27.7% | 52.9% | Not yet published | 70.1% | 39.5%Run by Artificial AnalysisIFBench |
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| Llama 4 Maverick | Not yet published | 31.7% | 20.6%Run by Epoch AIOTIS Mock AIME 2024-2025 | 67% | 4.9% | 0.2% | Not yet published | 50% | 62.1% | Not yet published | 58.3% | 43%Run by Artificial AnalysisIFBench |
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| 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%
- Qwen3.8 Max38.9%
- GLM-5.338.9%
- 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%
- Qwen3.8 Max65.6%
- Claude Sonnet 565.6%
- 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%
- Qwen3.8 Max43.1%
- Grok 4.743.1%
- 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%
- Qwen3.8 27B82%
- Claude Sonnet 582%
- GPT-5.482%
- Gemini 3.1 Pro Preview82%
- Gemini 3.8 Flash81.3%
- GPT-6 Astra80.7%
- Muse Wonder80.7%
- Qwen3.8 Max80.3%
- DeepSeek V4 Pro80.3%
- Grok 4.680.3%
- 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 Qwen3.8 Max 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 | Qwen3.8 Max | 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. | 984K | Artificial Analysis | Oct 27, 2026 | |
| Max outputThe most tokens the model writes in one response. | 131K | no Alibaba figure in the stored maker sources; OpenRouter lists 131,072 | OpenRouter | Oct 29, 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. | Alibaba Cloud International Website Product Terms of Service | its section 4.48 covers Model Studio, which serves qwen3.8-max | Alibaba Cloud | 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. | 5 of 19 | GILD route matrix | Oct 29, 2026 | |
| Cost | ||||
| Answer tokens per taskLower is better. Answer tokens per Intelligence Index task, reasoning excluded. | 36,900 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, cache readsLower is better. The cache-read share of AA's cost per Intelligence Index task. | $2.96 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, cache writesLower is better. The cache-write share of AA's cost per Intelligence Index task. | $1.76 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, inputLower is better. The input-token share of AA's cost per Intelligence Index task. | $4.76 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, outputLower is better. The answer-token share of AA's cost per Intelligence Index task. | $0.65 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Cost per task, reasoningLower is better. The reasoning-token share of AA's cost per Intelligence Index task. | $0.42 | Qwen3.8 Max (0902) | 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. | $5.41 | Qwen3.8 Max (0902) | 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. | $4,935 | Qwen3.8 Max (0902) | 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. | 107,730 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Reasoning tokens per taskLower is better. Reasoning tokens per Intelligence Index task. | 70,830 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Speed | ||||
| End-to-end time, 100K promptLower is better. Median seconds for a whole response with a 100,000-token prompt. | 66 s | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| End-to-end response timeLower is better. Seconds AA measures for a whole response on its standard prompt. | 64 s | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Time to first answer token, 100K promptLower is better. Median seconds to the first answer token with a 100,000-token prompt. | 55 s | Qwen3.8 Max (0902) | 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. | 52 s | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Output speed, 100K promptMedian output tokens per second when the prompt is about 100,000 tokens long. | 43 tokens/s | Qwen3.8 Max (0902) | 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. | 41 tokens/s | Qwen3.8 Max (0902) | 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. | 1,975 s | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Time to first token, 100K promptLower is better. Median seconds to the first chunk when the prompt is about 100,000 tokens long: long-input latency, separate from window size. | 8.2 s | Qwen3.8 Max (0902) | 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. | 2.9 s | Qwen3.8 Max (0902) | 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. | 27.1% | Extra-high effort | Artificial Analysis | Oct 29, 2026 |
| Omniscience accuracyShare of AA-Omniscience knowledge questions answered correctly. | 29.5% | Extra-high effort | Artificial Analysis | Oct 29, 2026 |
| Omniscience indexAA-Omniscience index: correct answers minus wrong answers, declines neutral, -100 to 100. | 12 | Qwen3.8 Max (0902) | 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. | 47.3% | Extra-high effort | Epoch AI | Sep 2, 2026 |
| Knowledge work | ||||
| AA-BriefcaseAA-Briefcase overall Elo for long business deliverables, with AA's 95% interval. | 1,608 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| AnalystAgent (AA run)AA's AnalystAgent score for analyst workflows. | 45% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| APEX-Agents (AA run)AA's run of APEX-Agents professional tasks. | 42.4% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| APEX-Agents (maintainers)APEX-Agents pass@1 from the maintainers, as Epoch AI republishes it. | 63.3% | Mercor (via Epoch AI) | Oct 26, 2026 | |
| GDP-PDF (AA run)Share of GDP-PDF document tasks where every check passes. | 22.8% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| GDPval-AAGDPval-AA Elo: AA's run of economically valuable knowledge-work tasks, graded pairwise, with AA's interval. | 1,673 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| MLCR (AA run)AA's MLCR overall score for long, multi-document reading. | 20% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Capability beyond the chart | ||||
| AA-LCRAA long-context reasoning accuracy. | 80.3% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Chess puzzles (Epoch)Share of chess puzzles solved, Epoch AI's run. | 37% | Extra-high effort | Epoch AI | Oct 13, 2026 |
| CritPt (AA run)Share of CritPt research-level physics problems solved in AA's run. | 17.7% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| DeepSWEDeepSWE pass@1, as Epoch AI republishes it. | 57.5% | Extra-high effort | Datacurve (via Epoch AI) | Oct 26, 2026 |
| DTBenchDTBench accuracy, as Epoch AI republishes it. | 92% | Extra-high effort | Redwood Research (via Epoch AI) | Oct 26, 2026 |
| EnterpriseOps-Gym (AA run)AA's EnterpriseOps-Gym score for enterprise operations agents. | 47.6% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| FrontierCode (AA run)AA's FrontierCode score: hard, unsaturated coding tasks. | 43.2% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| FrontierMath Tier 4 (Epoch)Share of FrontierMath Tier 4 research math problems solved, Epoch AI's run. | 34.1% | Extra-high effort | Epoch AI | Sep 2, 2026 |
| FrontierMath Tiers 1 to 3 (Epoch)Share of FrontierMath Tiers 1 to 3 problems solved, Epoch AI's run. | 65.6% | Extra-high effort | Epoch AI | Sep 2, 2026 |
| FrontierSWEFrontierSWE score, as Epoch AI republishes it. | 17.8% | Extra-high effort | FrontierSWE (via Epoch AI) | Oct 26, 2026 |
| GPQA Diamond (AA run)GPQA Diamond accuracy in AA's run. | 92.8% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| GPQA Diamond (Epoch)GPQA Diamond accuracy, best scorer, Epoch AI's run. | 92.3% | Extra-high effort | Epoch AI | Sep 2, 2026 |
| Humanity's Last Exam (AA run)Share of Humanity's Last Exam questions answered correctly in AA's run. | 43.1% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Intelligence IndexArtificial Analysis Intelligence Index: AA's composite of its own evaluation runs, 0 to 100 points. | 45.4 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| IT-Bench SRE (AA run)AA's IT-Bench SRE score for incident and reliability agents. | 40.3% | Qwen3.8 Max (0902) | 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. | 46.2 | Extra-high effort | Redwood Research (via Epoch AI) | Oct 26, 2026 |
| MMMU-Pro (AA run)Multimodal understanding accuracy on MMMU-Pro in AA's run. | 82.8% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Mystery game puzzles (Epoch)Share of mystery game puzzles solved, Epoch AI's run. | 38% | Extra-high effort | Epoch AI | Aug 5, 2026 |
| OTIS Mock AIME (Epoch)Share of OTIS Mock AIME 2024 to 2025 problems solved, Epoch AI's run. | 100% | Extra-high effort | Epoch AI | Sep 2, 2026 |
| ProofBenchShare of ProofBench proofs graded correct, from Vals AI as Epoch AI republishes it. | 58% | Vals AI (via Epoch AI) | Oct 26, 2026 | |
| SciCode (AA run)SciCode subproblem accuracy in AA's run. | 52.1% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| tau-Banking (AA run)AA's tau-Banking tool-use score. | 47.8% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Terminal-Bench 4.0 (AA run)Share of Terminal-Bench 4.0 tasks solved in AA's own harness. | 38.9% | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Terminal-Bench Science (AA run)Share of Terminal-Bench Science tasks solved in AA's harness. | 11.9% | Qwen3.8 Max (0902) | 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. | 1,671 | LMArena (via Epoch AI) | Oct 26, 2026 | |
| Domains | ||||
| EconomicsArtificial Analysis capability score for economics questions, 0 to 100 points. | 52.3 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| EngineeringArtificial Analysis capability score for engineering questions, 0 to 100 points. | 46.4 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Finance and accountingArtificial Analysis capability score for finance and accounting questions, 0 to 100 points. | 45.6 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Healthcare and medicalArtificial Analysis capability score for healthcare and medical questions, 0 to 100 points. | 41.4 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| LegalArtificial Analysis capability score for legal questions, 0 to 100 points. | 46.1 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
| Strategy and operationsArtificial Analysis capability score for strategy and operations questions, 0 to 100 points. | 47.3 | Qwen3.8 Max (0902) | Artificial Analysis | Oct 27, 2026 |
Routes, prices and uptime
Where Qwen3.8 Max is offered, what each route charges, and how each endpoint is holding up.
Where it is offered
5 of 19 routes GILD tracks offer Qwen3.8 Max today, preview included. Read Oct 29, 2026 from each route's own pages.
| Route | Status | Model ID | Limits and lifecycle | Sources |
|---|---|---|---|---|
| Claude Code | Available | qwen3.8-max | Alibaba Cloud documents this route, and Anthropic doesn't: its Model Studio example sets qwen3.8-max as the Opus model | Alibaba CloudAnthropic |
| Codex | Available | qwen3.8-max | Alibaba Cloud documents this as a Codex model provider (Responses API), and OpenAI doesn't | Alibaba CloudOpenAI |
| The maker's own API | Available | qwen3.8-maxqwen3.8-max-0902 | Alibaba Cloud Model Studio; qwen3.8-max moved to the qwen3.8-max-0902 snapshot effective September 5, 2026, at unchanged prices; International deployment US$2 input, US$6 output per million tokens up to 1M input tokens | Alibaba Cloud, Model inference pricingAlibaba Cloud, [Model Studio] Update Notice for Qwen3.8-Max Models |
| GitHub Models | Retired | not applicableservice retired | service retired July 30, 2026 | GitHub |
| OpenCode | Available | qwen3.8-max | OpenCode Zen chat-completions endpoint and OpenCode Go; US$2 input, US$6 output; OpenCode names no snapshot | OpenCode, ModelsOpenCode, Go |
| OpenRouter | Available | qwen/qwen3.8-max-0902 | 1,000,000 context for the model; top provider 131,072 output | OpenRouter |
Not offered on 10 routes: Amazon Bedrock, Antigravity, Claude on Google Cloud (Anthropic managed), Claude Platform on AWS, Cursor, Databricks, GitHub Copilot, Google Cloud Vertex / Agent Platform (Google managed), Microsoft Foundry and Snowflake Cortex.
3 routes do not say: Gemini CLI, Grok Build and Windsurf / Devin.
What each of these 13 routes' pages say, with sources
| Route | Status | Model ID | Limits and lifecycle | Sources |
|---|---|---|---|---|
| Amazon Bedrock | Not offered | Bedrock lists Qwen3 235B, Qwen3 32B, Qwen3 Coder and Qwen3 Next models; Qwen3.8 Max isn't among them | Amazon Web Services | |
| Antigravity | Not offered | Antigravity lists Gemini, Claude and GPT-OSS models only | ||
| Claude on Google Cloud (Anthropic managed) | Not offered | Takes the Claude API's model IDs, which name Anthropic's Claude models only | Anthropic, Claude Models on Google Cloud (Anthropic managed)Anthropic, Models overview | |
| Claude Platform on AWS | Not offered | Claude Platform on AWS lists Anthropic's Claude models only | Anthropic | |
| Cursor | Not offered | absent from Cursor's model table | Cursor | |
| Databricks | Not offered | Databricks lists Qwen3.5 and Qwen3-Next models; Qwen3.8 Max isn't among them | Databricks | |
| GitHub Copilot | Not offered | Absent from the Copilot supported-models table, which lists each supported model | GitHub | |
| Google Cloud Vertex / Agent Platform (Google managed) | Not offered | Google lists Qwen 3 Next, Qwen 3 Coder and Qwen 3 235B; Qwen3.8 Max isn't among them | Google Cloud | |
| Microsoft Foundry | Not offered | Foundry's Qwen models are Qwen3-32B, Qwen3.6-35B-A3B and Qwen3.8-27B; Qwen3.8 Max isn't among them | Microsoft | |
| Snowflake Cortex | Not offered | Cortex lists Qwen3 32B, Qwen3 Next 80B and Qwen3 VL 235B; Qwen3.8 Max isn't among them | Snowflake | |
| Gemini CLI | Not stated | Gemini CLI's model page names Gemini models only | ||
| Grok Build | Not stated | Grok Build names only grok-4.7; its docs say it supports any custom model added to its config file | xAI (SpaceXSI), Grok Build: SpaceXSI's Coding AgentxAI (SpaceXSI), Bring Grok to | |
| Windsurf / Devin | Not stated | absent from Devin model data | Cognition |
Prices by route
The lowest standard rate is Alibaba Cloud Model Studio, at $2 / $6 per million input and output tokens. US dollars per million tokens, as each route lists them, one row per route and rate plan, cheapest standard rate first after the maker's own; a blended rate states its mix. OpenRouter's endpoints follow under one heading, each with its monitor's uptime over 1 day and 30 minutes and the context and output it serves.
| Route | Standard, in / out | Cache read | Other rates | Source, or uptime (1 day / 30 min) and limits |
|---|---|---|---|---|
| Alibaba Cloud Model StudioMakerLowest | $2 / $6 | Alibaba Cloud, Oct 29, 2026 | ||
| Artificial Analysis price record | $2 / $6 | $0.25 | Blended $3, 3 input : 1 output, no cacheBlended $1.18, 7 cache-hit : 2 input : 1 output | Artificial Analysis, Oct 27, 2026 |
| OpenRouter | $2 / $6 | $0.25 | OpenRouter, Oct 29, 2026 | |
| Through OpenRouter, 2 provider endpoints. OpenRouter, Oct 30, 2026 | ||||
| Alibaba | $2 / $6 | $0.25 | Cache write $2.50, 5-minute cache | Up 99.9% / 100%1M context, 131K output |
| Alibaba (us-east-1) | $2 / $6 | $0.25 | Up 99.8% / 100%1M context, 131K output | |
Lineup
Alibaba's 2 releases in 1 family, oldest to newest along each tier, with list price and speed. Qwen3.8 Max 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 28, 2026 and Nov 2, 2026.
Qwen
Alibaba's Qwen family of open-weight and hosted models.
2 releases
- This page3.8Current. In 2 products we coverPrice$2 / $6Speed40.3 tok/s
- 3.8Current. In no product we cover yetPrice$0.50 / $3Speed38.3 tok/s
Where it fits
The layers of Agentic Software Development that Qwen3.8 Max can power. A product supplies the rest.
Product & Engineering, Software Development
Agentic Software Development
- Primary role
- Foundation Model / Reasoning Engine
Qwen3.8 Max can power coding, reasoning, and validation work inside an agentic software-development product. The Model does not itself provide the surrounding interface, execution environment, or system of record.
- Supporting
Work planning & task decomposition
The Model can assist with work planning & task decomposition when a Product supplies the necessary context and tools.
- Supporting
Codebase context & intelligence
The Model can assist with codebase context & intelligence when a Product supplies the necessary context and tools.
- Supporting
Coding & implementation
The Model can assist with coding & implementation when a Product supplies the necessary context and tools.
- Supporting
Debugging & investigation
The Model can assist with debugging & investigation when a Product supplies the necessary context and tools.
- Supporting
Testing & verification
The Model can assist with testing & verification when a Product supplies the necessary context and tools.
- Supporting
Code review & quality
The Model can assist with code review & quality when a Product supplies the necessary context and tools.
Products
We cover 2 products that offer Qwen3.8 Max today, all subscriptions.
Through a subscription
Limits each vendor states
- ClineClinePass
- 2 to 5 times the usage the standard API rate buys on popular open coding models, measured against a 5-hour rolling window, a weekly limit and a monthly limit; Cline publishes no figures for those limits.
Plan access as each vendor's page states it: Anomaly (Oct 28, 2026), Cline (Oct 28, 2026).
What practitioners report
Qwen3.8 Max has enough accounts to score 1 of 7 axes so far.
Each figure is the share of accounts naming Qwen3.8 Max that speak well of it on that axis. An axis is scored once praise and concerns are both on record from at least five accounts by three authors. An account from the maker, a company that sells or serves the model, or the maker's expert program is listed and counts toward no figure.
| Axis | Favorable | Accounts |
|---|---|---|
| Quality and reasoningWhether its answers and code are right on the author's own task: reasoning, accuracy, instruction following, and consistency. | 57% | 4 favorable, 3 not, 7 authors |
| Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track. | Only praise on record | 1 favorable, 0 not, 1 author |
| Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs. | Only praise on record | 1 favorable, 0 not, 1 author |
| Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers. | Only concerns on record | 0 favorable, 1 not, 1 author |
| CostWhat the work costs: price per task, token use, and what caching and batch save. | Only concerns on record | 0 favorable, 2 not, 2 authors |
| SpeedResponse time, time to first token, and throughput. | Needs 5 accounts from 3 authors | 1 favorable, 3 not, 4 authors |
| ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked. | Only concerns on record | 0 favorable, 1 not, 1 author |
Every model on these seven axes
| Axis | Qwen3.8 Max | Qwen3.8 27B | 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 Haiku 4.5 | Claude Sonnet 4.5 | GPT-6.1 Terra | GPT-6.1 Sol | GPT-6 Luna | GPT-6 Astra | GPT-5.6 Sol | GPT-5.6 Terra | GPT-5.6 Luna | GPT-5.5 | GPT-5.4 | gpt-oss-120b | GPT-6 Sol | GPT-5.3-Codex | Gemini 4 Argon | Gemini 3.8 Flash | Gemma 4 31B | Gemini 3.1 Pro Preview | Gemini 3.6 Flash | DeepSeek V4.1 Flash | DeepSeek V4 Pro | Kimi K3.1 Pro | Kimi K3 | Kimi K2.7 Code | Mistral Large 4 | Mistral Medium 3.5 | Grok 4.7 | Grok 4.6 | Grok 4.5 | MiniMax M3.1 Flash | Mercury 3 | GLM-5.3-Flash | GLM-5.3 | GLM-5.2 | Muse Spark Open | Muse Wonder | Muse Spark 1.3 | Llama 4 Scout | Llama 4 Maverick | MiMo-V2.6-Pro | MiMo-V2.6-Flash | Ling 3.1 Flash | Step 5 Preview |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Quality and reasoning | 57%4 favorable, 3 not, 7 authors | 71%24 favorable, 10 not, 34 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 | 58%14 favorable, 10 not, 24 authors | 69%11 favorable, 5 not, 16 authors | 33%3 favorable, 6 not, 8 authors | 55%12 favorable, 10 not, 22 authors | 55%16 favorable, 13 not, 29 authors | 44%12 favorable, 15 not, 26 authors | 33%3 favorable, 6 not, 9 authors | 38%3 favorable, 5 not, 8 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | 33%4 favorable, 8 not, 12 authors | 33%2 favorable, 4 not, 6 authors | 58%22 favorable, 16 not, 38 authors | 31%10 favorable, 22 not, 32 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 63%22 favorable, 13 not, 35 authors | 56%27 favorable, 21 not, 45 authors | 80%24 favorable, 6 not, 28 authors | 56%20 favorable, 16 not, 36 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 61%25 favorable, 16 not, 40 authors | Only concerns on record0 favorable, 4 not, 4 authors | 59%20 favorable, 14 not, 32 authors | Only praise on record3 favorable, 0 not, 3 authors | 50%3 favorable, 3 not, 6 authors | 58%11 favorable, 8 not, 18 authors | 36%5 favorable, 9 not, 14 authors | 43%16 favorable, 21 not, 36 authors | 86%6 favorable, 1 not, 7 authors | 60%3 favorable, 2 not, 5 authors | 62%13 favorable, 8 not, 21 authors | 86%18 favorable, 3 not, 21 authors | 67%14 favorable, 7 not, 21 authors | 76%47 favorable, 15 not, 61 authors | 71%5 favorable, 2 not, 7 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 20%1 favorable, 4 not, 5 authors | Only praise on record2 favorable, 0 not, 2 authors | 53%8 favorable, 7 not, 15 authors | 44%8 favorable, 10 not, 17 authors | 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 | Only praise on record1 favorable, 0 not, 1 author | 46%6 favorable, 7 not, 13 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 | 43%3 favorable, 4 not, 6 authors | 50%3 favorable, 3 not, 6 authors | 40%2 favorable, 3 not, 5 authors | 40%4 favorable, 6 not, 10 authors | 33%3 favorable, 6 not, 9 authors | 62%8 favorable, 5 not, 13 authors | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author | No accounts yet | 27%4 favorable, 11 not, 15 authors | 56%5 favorable, 4 not, 9 authors | No accounts yet | 25%2 favorable, 6 not, 8 authors | 47%7 favorable, 8 not, 15 authors | 67%4 favorable, 2 not, 6 authors | 54%7 favorable, 6 not, 12 authors | Only concerns on record0 favorable, 1 not, 1 author | 59%10 favorable, 7 not, 17 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | 38%5 favorable, 8 not, 13 authors | Only concerns on record0 favorable, 5 not, 5 authors | 38%6 favorable, 10 not, 16 authors | Only praise on record2 favorable, 0 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | 67%4 favorable, 2 not, 6 authors | 80%8 favorable, 2 not, 10 authors | 33%2 favorable, 4 not, 6 authors | 57%4 favorable, 3 not, 7 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | Only concerns on record0 favorable, 4 not, 4 authors | 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 | Only praise on record1 favorable, 0 not, 1 author | 75%6 favorable, 2 not, 8 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 | 40%2 favorable, 3 not, 5 authors | 50%4 favorable, 4 not, 8 authors | Only concerns on record0 favorable, 1 not, 1 author | 38%3 favorable, 5 not, 8 authors | 20%1 favorable, 4 not, 5 authors | 27%3 favorable, 8 not, 11 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 25%2 favorable, 6 not, 8 authors | Only concerns on record0 favorable, 3 not, 3 authors | No accounts yet | 25%2 favorable, 6 not, 8 authors | 38%5 favorable, 8 not, 13 authors | 20%1 favorable, 4 not, 5 authors | 44%7 favorable, 9 not, 16 authors | Only praise on record1 favorable, 0 not, 1 author | 58%7 favorable, 5 not, 12 authors | No accounts yet | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | Only praise on record1 favorable, 0 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | No accounts yet | 42%5 favorable, 7 not, 12 authors | No accounts yet | No accounts yet | 40%2 favorable, 3 not, 5 authors | 60%3 favorable, 2 not, 5 authors | No accounts yet | 40%2 favorable, 3 not, 5 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 3 not, 3 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 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 | Only concerns on record0 favorable, 1 not, 1 author | 17%1 favorable, 5 not, 6 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 | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 authors | 50%3 favorable, 3 not, 6 authors | Only concerns on record0 favorable, 2 not, 2 authors | 27%3 favorable, 8 not, 11 authors | 25%2 favorable, 6 not, 8 authors | 41%7 favorable, 10 not, 17 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | No accounts yet | No accounts yet | 14%1 favorable, 6 not, 7 authors | 25%3 favorable, 9 not, 12 authors | No accounts yet | 33%3 favorable, 6 not, 9 authors | 39%7 favorable, 11 not, 17 authors | Only concerns on record0 favorable, 7 not, 7 authors | 40%8 favorable, 12 not, 20 authors | No accounts yet | 35%8 favorable, 15 not, 23 authors | No accounts yet | 9%1 favorable, 10 not, 11 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | 13%2 favorable, 14 not, 16 authors | Only concerns on record0 favorable, 9 not, 9 authors | 25%5 favorable, 15 not, 20 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 7 not, 7 authors | 11%1 favorable, 8 not, 9 authors | Only concerns on record0 favorable, 3 not, 3 authors | 33%5 favorable, 10 not, 15 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 6 not, 6 authors | Only concerns on record0 favorable, 1 not, 1 author | 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 | Only concerns on record0 favorable, 2 not, 2 authors | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 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 | 29%4 favorable, 10 not, 12 authors | 38%3 favorable, 5 not, 8 authors | 80%8 favorable, 2 not, 9 authors | 74%14 favorable, 5 not, 19 authors | 79%22 favorable, 6 not, 26 authors | 29%7 favorable, 17 not, 23 authors | 57%4 favorable, 3 not, 7 authors | Only concerns on record0 favorable, 1 not, 1 author | 50%3 favorable, 3 not, 6 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 63%5 favorable, 3 not, 8 authors | 60%3 favorable, 2 not, 5 authors | 55%12 favorable, 10 not, 21 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 35%7 favorable, 13 not, 20 authors | 58%14 favorable, 10 not, 23 authors | Only praise on record7 favorable, 0 not, 7 authors | 50%8 favorable, 8 not, 16 authors | Only concerns on record0 favorable, 1 not, 1 author | 66%25 favorable, 13 not, 37 authors | Only praise on record2 favorable, 0 not, 2 authors | 40%10 favorable, 15 not, 25 authors | 71%5 favorable, 2 not, 7 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 27%3 favorable, 8 not, 11 authors | Only concerns on record0 favorable, 8 not, 8 authors | 19%5 favorable, 21 not, 26 authors | 20%1 favorable, 4 not, 5 authors | Only praise on record4 favorable, 0 not, 4 authors | 80%12 favorable, 3 not, 15 authors | 50%6 favorable, 6 not, 12 authors | 76%16 favorable, 5 not, 21 authors | 35%8 favorable, 15 not, 23 authors | 71%5 favorable, 2 not, 7 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 9 not, 9 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 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 | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 33%7 favorable, 14 not, 21 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 | 78%7 favorable, 2 not, 9 authors | 75%6 favorable, 2 not, 8 authors | 83%5 favorable, 1 not, 5 authors | 37%7 favorable, 12 not, 19 authors | 45%5 favorable, 6 not, 11 authors | 41%7 favorable, 10 not, 17 authors | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 80%4 favorable, 1 not, 5 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | No accounts yet | 85%23 favorable, 4 not, 27 authors | 57%4 favorable, 3 not, 7 authors | Only praise on record1 favorable, 0 not, 1 author | 45%5 favorable, 6 not, 11 authors | 61%19 favorable, 12 not, 31 authors | 53%10 favorable, 9 not, 17 authors | 35%6 favorable, 11 not, 16 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 68%21 favorable, 10 not, 30 authors | Only concerns on record0 favorable, 1 not, 1 author | 21%4 favorable, 15 not, 19 authors | Only concerns on record0 favorable, 2 not, 2 authors | No accounts yet | 21%3 favorable, 11 not, 14 authors | Only concerns on record0 favorable, 2 not, 2 authors | 29%5 favorable, 12 not, 17 authors | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | Only praise on record2 favorable, 0 not, 2 authors | 44%4 favorable, 5 not, 9 authors | 65%13 favorable, 7 not, 20 authors | 33%3 favorable, 6 not, 9 authors | 20%3 favorable, 12 not, 15 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | No accounts yet | 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 | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 9 not, 9 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 | 29%2 favorable, 5 not, 7 authors | 40%4 favorable, 6 not, 10 authors | Only concerns on record0 favorable, 1 not, 1 author | 13%1 favorable, 7 not, 8 authors | Only concerns on record0 favorable, 5 not, 5 authors | 14%2 favorable, 12 not, 14 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 4 not, 4 authors | 17%1 favorable, 5 not, 6 authors | Only concerns on record0 favorable, 3 not, 3 authors | 5%1 favorable, 18 not, 19 authors | 15%3 favorable, 17 not, 20 authors | Only concerns on record0 favorable, 5 not, 5 authors | 14%3 favorable, 19 not, 22 authors | Only concerns on record0 favorable, 1 not, 1 author | 42%5 favorable, 7 not, 12 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 8%1 favorable, 12 not, 13 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 38%3 favorable, 5 not, 8 authors | Only concerns on record0 favorable, 4 not, 4 authors | 22%2 favorable, 7 not, 9 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | 60%3 favorable, 2 not, 5 authors | 33%2 favorable, 4 not, 5 authors | Only concerns on record0 favorable, 7 not, 7 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 2 not, 2 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author |
The 12 accounts behind Qwen3.8 Max's figures
GILD searched Hacker News, GitHub, Reddit, X and the web for accounts that name Qwen3.8 Max.
Quality and reasoning 57%
- Unfavorable
Qwen 3.8 Max doesn't check its work and leaves stuff broken, doesn't write tests unless prompted
DeepSeek V4 Flash 0731. SwellJoe, Hacker News commenter who uses Chinese models over the API, self-described, Aug 7, 2026. Qwen3.8 Max, written Qwen 3.8 Max, among the Chinese models the author uses over the API.
- Favorable
Qwen 3.8 Max 0902 | Fast and intelligent, better than Kimi K3
Root shell on Samsung TV. nekitamo, Hacker News commenter who ran a crackme reverse-engineering benchmark across top models, self-described, Oct 24, 2026. Qwen3.8 Max, listed as Qwen 3.8 Max 0902, through OpenRouter credits in Claude Code, reverse engineering a small crackme with Ghidrasql.
- Favorable
The 3.8 Max fixed exactly that. It used the real API end to end
LLM Benchmarks: Qwen 3.8, GLM 5.3, Gemini 3.7, Grok 4.6. Fabio Akita, who runs the open llm-coding-benchmark and writes AkitaOnRails, self-described, Aug 15, 2026. Qwen3.8 Max, written Qwen 3.8 Max, in OpenCode on his v2 coding benchmark, building a RubyLLM chat app.
- Favorable
C (spec/plan prompt, qwen3.8-max) 18 (62%), 0 clearly false.
Spec/plan review mode on a stronger model (from #143 evidence). lhpaul, owner of the Ronda GitHub PR review bot, self-described, Oct 6, 2026. qwen3.8-max (the endpoint reports the qwen3.8-max-0902 alias) as the reviewer model for spec and plan pull requests in the Ronda review bot.
- Unfavorable
Qwen 3.8 Max 32% -11 kcal 48 kcal
Nutrition estimates from meal photos, 25 meals. mr_tolkien, a Reddit user, self-described, Sep 7, 2026. Qwen3.8 Max through OpenCode Go or OpenRouter on 25 Nutrition5k meals with a USDA and MEXT lookup tool, scored on the share within 20% error.
- Favorable
The improvement was quite large: previous Qwen3.8-Max: 74/98 Qwen3.8-Max-0902: 86/98 Most of that gain came from visual tasks: overall visual: 35/59 → 48/59 Visual1: 19/33 → 27/33 Visual2: 16/26 → 21/26 spatial awareness: 12/17 on the new run
Qwen3.8-Max-0902 on MindTrial. Correct_Tomato1871, a Reddit user who runs the MindTrial evaluation, self-described, Sep 8, 2026. Qwen3.8-Max-0902 against the earlier Qwen3.8-Max on MindTrial's 98 tasks.
- Favorable
I tried to make Fable implement an FEM based brushless motor simulation model. From generating the LUTs with python to using the LUTs in runtime in Godot. Because it's highly theoretical work and can't be just "tested" by a python script, it heavily relies on world knowledge. I could always find mistakes on Fable's (or Kimi) final equations or theory. A simple sign mistake to actually using the wrong formula etc... As far as I can test/see, Qwen3.8-max is yet to make a single mistake on this kind of workload.
Qwen3.8-max on theory-heavy simulation work. almbfsek, a Reddit user, self-described, Aug 18, 2026. Qwen3.8-max implementing an FEM-based brushless motor simulation, from lookup tables in Python to runtime use in Godot, against Fable and Kimi.
- Unfavorable
same prompt, same image, same settings: one run matched 3 of 5 logos. the next run matched 0 of 5. nothing changed between calls
The visual grounding evaluation of Qwen3.8-Max that nobody wanted. datascienceharp, a Reddit user, self-described, Aug 7, 2026. Qwen3.8-Max drawing bounding boxes on 27,083 annotated logos, scored against the annotations.
Tool use and structured output Only praise on record
- Favorable
All three models passed all 18 tasks, with no loops or stalls.
Benchmark: Bonsai 2 27B, Qwen3.8 27B, and Qwen3.8 Max on the 18-task suite. alex-alecu, collaborator on the Garden Desk document agent repo, self-described, Sep 23, 2026. Qwen3.8 Max through OpenRouter, thinking on, on Garden Desk's 18-task document agent suite.
Long context Only praise on record
- Favorable
there were signs it had good vision
Qwen3.8-Max: A New Bar for Coding and Cowork. jjcm, Hacker News commenter who runs image-to-HTML tests, self-described, Aug 3, 2026. Qwen3.8 Max, written Qwen 3.8 max, in OpenCode on an image-to-HTML build of rich designs as a SPA, with the same prompt given to Opus 5.
Developer experience Only concerns on record
- Unfavorable
That looks like three settings, not five
qwen/qwen3.8-max-0902: which native reasoning_effort do "minimal" and "high" map to?. mauricekleine, who runs the Nonobench puzzle benchmark, self-described, Sep 27, 2026. Qwen3.8 Max (qwen/qwen3.8-max-0902) through OpenRouter, served by Alibaba, at five reasoning efforts on 30 puzzles.
Cost Only concerns on record
- Unfavorable
but token-hungry. | 1,305,241 | 26,390 | $0.25
Root shell on Samsung TV. nekitamo, Hacker News commenter who ran a crackme reverse-engineering benchmark across top models, self-described, Oct 24, 2026. Qwen3.8 Max, listed as Qwen 3.8 Max 0902, through OpenRouter credits in Claude Code, reverse engineering a small crackme with Ghidrasql.
- Unfavorable
verbose: 25 million tokens
LLM Benchmarks: Qwen 3.8, GLM 5.3, Gemini 3.7, Grok 4.6. Fabio Akita, who runs the open llm-coding-benchmark and writes AkitaOnRails, self-described, Aug 15, 2026. Qwen3.8 Max, written Qwen 3.8 Max, in OpenCode on his v2 coding benchmark, building a RubyLLM chat app.
Speed Needs 5 accounts from 3 authors
- Unfavorable
Claude finished in around 16 min, but I spent close to 2 hours shepherding the Qwen build.
Qwen3.8-Max: A New Bar for Coding and Cowork. jjcm, Hacker News commenter who runs image-to-HTML tests, self-described, Aug 3, 2026. Qwen3.8 Max, written Qwen 3.8 max, in OpenCode on an image-to-HTML build of rich designs as a SPA, with the same prompt given to Opus 5.
- Favorable
Qwen 3.8 Max 0902 | Fast and intelligent
Root shell on Samsung TV. nekitamo, Hacker News commenter who ran a crackme reverse-engineering benchmark across top models, self-described, Oct 24, 2026. Qwen3.8 Max, listed as Qwen 3.8 Max 0902, through OpenRouter credits in Claude Code, reverse engineering a small crackme with Ghidrasql.
- Unfavorable
Cost: ~11 min/pass, 13-25 findings/pass, vs ~10 s and 3-5 for B.
Spec/plan review mode on a stronger model (from #143 evidence). lhpaul, owner of the Ronda GitHub PR review bot, self-described, Oct 6, 2026. qwen3.8-max (the endpoint reports the qwen3.8-max-0902 alias) as the reviewer model for spec and plan pull requests in the Ronda review bot.
- Unfavorable
Loving the output quality so far, but I'm in the central US connecting to their Singapore endpoint and seeing some noticeable per-call latency (individual tool/reasoning calls in the 15-25s range).
Qwen3.8-Max latency from US. Low-Isopod3776, a Reddit user, self-described, Sep 3, 2026. Qwen3.8-Max on a mid-tier individual plan from the central US through Alibaba's Singapore endpoint.
Reliability Only concerns on record
- Unfavorable
I encountered a significant amount of errors / timeouts while it was running.
Qwen3.8-Max: A New Bar for Coding and Cowork. jjcm, Hacker News commenter who runs image-to-HTML tests, self-described, Aug 3, 2026. Qwen3.8 Max, written Qwen 3.8 max, in OpenCode on an image-to-HTML build of rich designs as a SPA, with the same prompt given to Opus 5.