Qwen3.5 397B
AlibabaOpen weightsNon-reasoningProvisionalReleased Feb 16, 2026
Overall score
55.4
Rank 66 of 222 · 41.1–69.8
Context window
128K
128,000 tokens
Price per 1M tokens
$0.60 in · $3.60 out
Source: BenchLM
Blended price
$1.35
3:1 input:output tokens
Output speed
—
Not measured yet
Category scores
Scores per capability area with the model's rank among ranked models in that category.
- 1Multilingual#593.8
- 2Math81.7
- 3Instruction following#5979.9
- 4Reasoning74.1
- 5Multimodal#2973.6
- 6Knowledge#7061.2
- 7Coding41.7
- 8Agentic & tool use#6239.9
Benchmark results (61)
As reported in system cards, papers and public evaluations. Position compares this model with every other model reporting the same benchmark.
Multimodal
| MMMU-Pro | 79.0 | #15 of 48 |
| CharXiv | 80.8 | #26 of 42 |
| MMMU | 85.0 | #4 of 21 |
| MathVision | 88.6 | #8 of 20 |
| SimpleVQA | 67.1 | #10 of 17 |
| RealWorldQA | 83.9 | #8 of 16 |
| ERQA | 67.5 | #8 of 16 |
| ScreenSpot Pro | 65.6 | #13 of 15 |
| VideoMMMU | 84.7 | #7 of 12 |
| V* | 95.8 | #3 of 12 |
| OmniDocBench 1.5 | 90.8 | #5 of 11 |
| Video-MME (with subtitle) | 87.5 | #6 of 11 |
| MLVU (M-Avg) | 86.7 | #3 of 9 |
| CountBench | 97.2 | #3 of 8 |
| RefCOCO (avg) | 92.3 | #2 of 8 |
| Video-MME (w/o subtitle) | 83.7 | #3 of 7 |
| CC-OCR | 82.0 | #1 of 7 |
| AI2D_TEST | 93.9 | #2 of 7 |
| DynaMath | 86.3 | #2 of 6 |
| We-Math | 87.9 | #1 of 5 |
| MMLongBench-Doc | 61.5 | #2 of 5 |
| ODINW13 | 47.0 | #3 of 4 |
Agentic & tool use
| Gert Labs | 46.76 | #27 of 52 |
| BrowseComp | 69.0 | #32 of 50 |
| MCP Atlas | 46.1 | #38 of 42 |
| Terminal-Bench 2.0 | 52.5 | #26 of 39 |
| Claw-Eval | 56.8 | #28 of 36 |
| OSWorld-Verified | 62.2 | #29 of 35 |
| τ³-bench results | 68.4 | #8 of 23 |
| Toolathlon | 36.3 | #19 of 22 |
| ResearchClawBench | 14.2 | #15 of 19 |
| WideResearch | 74.0 | #10 of 16 |
| VITA-Bench | 43.7 | #4 of 11 |
| QwenClawBench | 51.8 | #10 of 10 |
| DeepPlanning | 37.6 | #3 of 7 |
| MCP-Tasks | 74.2 | #1 of 5 |
Multilingual
| SWE Multilingual | 69.3 | #35 of 46 |
| MMLU-ProX | 84.7 | #4 of 16 |
| INCLUDE | 85.6 | #5 of 10 |
| NOVA-63 | 59.1 | #1 of 7 |
| PolyMath | 73.3 | #4 of 6 |
| MAXIFE | 88.2 | #3 of 5 |
Knowledge
| GPQA | 88.4 | #32 of 117 |
| HLE | 28.7 | #47 of 69 |
| MMLU-Pro | 87.8 | #5 of 67 |
| SuperGPQA | 70.4 | #9 of 20 |
| MMLU-Redux | 94.9 | #3 of 15 |
| C-Eval | 93.0 | #3 of 10 |
Math
| AIME26 | 93.3 | #18 of 29 |
| HMMT Feb 2026 | 87.9 | #9 of 24 |
| HMMT Feb 2025 | 94.8 | #6 of 13 |
| HMMT Nov 2025 | 92.7 | #6 of 12 |
| MMAnswerBench | 80.9 | #8 of 10 |
Coding
| SWE-bench Verified | 76.2 | #38 of 98 |
| SWE-bench Pro | 50.9 | #60 of 69 |
| LiveCodeBench v6 | 83.6 | #21 of 46 |
| NL2Repo | 32.2 | #29 of 31 |
Reasoning
| LongBench v2 | 63.2 | #4 of 17 |
| AI-Needle | 68.7 | #2 of 4 |
Instruction following
| IFEval | 92.6 | #11 of 53 |
| IFBench | 76.5 | #19 of 42 |
Pricing by source
USD per 1M tokens.
| Source | Input | Output | Cached in |
|---|---|---|---|
| List price (BenchLM) | $0.60 | $3.60 | — |
Alibaba Cloud Model Studio's pricing page lists qwen3.5-397b-a17b at $0.60 input / $3.60 output per million tokens in International deployment mode for prompts up to 256K tokens.
Speed
Measured by us through OpenRouter (median of trials).
Not available on OpenRouter, so we cannot measure it yet.
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