- MMLU-Pro 86.1
- MMLU-Redux 93.2
- C-Eval 90.5
- SuperGPQA 65.6
- IFEval 95
- IFBench 76.5
- MultiChallenge 60.8
- AA-LCR 66.1
- LongBench v2 60.6
- GPQA Diamond 85.5
- HMMT Feb 25 92
- HMMT Nov 25 89.8
- SWE-bench Verified 72.4
- Terminal Bench 2 41.6
- LiveCodeBench v6 80.7
- CodeForces 1899
- OJBench 40.1
- Mean of FullStackBench en 60.1 / FullStackBench zh 57.4 58.8
- BFCL-V4 68.5
- TAU2-Bench 79
- VITA-Bench 41.9
- DeepPlanning 22.6
- Browsecomp 61
- Browsecomp-zh 62.1
- WideSearch 61.1
- Seal-0 47.2
- MMMLU 85.9
- MMLU-ProX 82.2
- NOVA-63 58.1
- INCLUDE 81.6
- Global PIQA 87.5
- PolyMATH 71.2
- WMT24++ 77.6
- MAXIFE 88
- MMMU 82.3
- MMMU-Pro 75
- MathVision 86
- Mathvista(mini) 87.8
- DynaMath 87.7
- Best of ZEROBench / ZEROBench_sub 36.2 36.2
- VlmsAreBlind 96.9
- BabyVision 44.6 / 34.8 (with CI / without CI) 44.6
- RealWorldQA 83.7
- MMStar 81
- MMBench EN-DEV-v1.1 92.6
- SimpleVQA 56
- HallusionBench 70
- OmniDocBench1.5 88.9
- CharXiv(RQ) 79.5
- MMLongBench-Doc 60.2
- CC-OCR 81
- AI2D_TEST 92.9
- OCRBench 89.4
- ERQA 60.5
- CountBench 97.8
- RefCOCO(avg) 90.9
- ODInW13 41.1
- EmbSpatialBench 84.5
- RefSpatialBench 67.7
- LingoQA 82
- Hypersim 13
- SUNRGBD 35.4
- Nuscene 15.2
- Best of VideoMME(w sub.) / VideoMME(w/o sub.) 87.0 87
- VideoMMMU 82.3
- MLVU 85.9
- MVBench 74.6
- LVBench 73.6
- MMVU 73.3
- ScreenSpot Pro 70.3
- OSWorld-Verified 56.2
- AndroidWorld 64.2
- TIR-Bench 59.8 / 42.3 (with CI / without CI) 59.8
- V* 93.7 / 89.0 (with CI / without CI) 93.7
- SLAKE 80
- PMC-VQA 62.4
- MedXpertQA-MM 62.4
- HLE w/ CoT 24.3; HLE w/ tool 48.5 48.5
Qwen3.5-27B
Qwen3.5-27B ranks first on 3 of the 120 benchmarks with five or more models scored.
Qwen3.5-27B
Open weights
- MMMU-Pro 75% #41 /90
- IFBench 76.5% #19 /80
- AA-LCR (Artificial Analysis Long Context Reasoning) 66.1% #16 /38
Where it ranks
Its best score on each benchmark, and where that ranks among every model with a score there. We rank each model once, at its best setting.
Knowledge and language
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| IFEval | 95% | #7 of 135 | Lab model card | |
| MMLU-Pro | 86.1% | #19 of 167 | Lab model card | |
| IFMTBench | 81.1% | #1 of 8 | Official leaderboard | |
| HallusionBench | 70% | #4 of 31 | Lab model card | |
| QIMMA | 62% | #5 of 25 | Official leaderboard | |
| STALE | 31.3% | #2 of 10 | Official leaderboard | |
| Judgemark v2.1 | 84.3 | #9 of 42 | Official leaderboard | |
| BOUQuET | 31.2 | #4 of 18 | Official leaderboard | |
| Global PIQA | 78.5% | #10 of 44 | Official leaderboard | |
| IFBench | 76.5% | #19 of 80 | Lab model card | |
| SEA-HELM | 74.2 | #17 of 71 | Official leaderboard | |
| KINA | 39.4% | #10 of 37 | Official leaderboard | |
| Humanity's Last Exam | 48.5% | #45 of 154 | Lab model card | |
| MMLU-ProX | 82.2% | #7 of 23 | Lab model card | |
| INCLUDE | 81.6% | #10 of 31 | Lab model card | |
| MMLU-Redux | 93.2% | #15 of 45 | Lab model card | |
| SuperGPQA | 65.6% | #12 of 35 | Lab model card | |
| LMArena (Elo) | 1,409 | #123 of 335 | Official leaderboard | |
| C-Eval | 90.5% | #17 of 46 | Lab model card | |
| MMMLU | 85.9% | #27 of 71 | Lab model card | |
| LongBench v2 | 60.6% | #14 of 35 | Lab model card | |
| CulturalRiddles | 28% | #8 of 20 | Official leaderboard | |
| AA-LCR (Artificial Analysis Long Context Reasoning) | 66.1% | #16 of 38 | Lab model card | |
| MultiChallenge | 60.8% | #19 of 42 | Lab model card | |
| MAXIFE | 88% | #5 of 11 | Lab model card | |
| NOVA-63 | 58.1% | #5 of 11 | Lab model card | |
| Judgemark v4 | 60.5 | #19 of 40 | Official leaderboard | |
| Longform Creative Writing (EQ-Bench) | 59.0 | #65 of 119 | Official leaderboard | |
| Seal-0 | 47.2% | #4 of 7 | Lab model card | |
| Extended NYT Connections | 47.9% | #72 of 103 | Official leaderboard | |
| SimpleVQA | 56% | #23 of 30 | Lab model card | |
| Vectara Hallucination Leaderboard (2025 dataset) | 12.1% | #81 of 104 | Official leaderboard | |
| WideSearch | 61.1% | #16 of 19 | Lab model card |
Math and science
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| GPQA Diamond | 85.5% | #75 of 302 | Lab model card | |
| PolyMath | 71.2% | #6 of 24 | Lab model card | |
| HMMT 2025 | 92% | #20 of 54 | Lab model card | |
| DTBench | 82.4% | #82 of 180 | Official leaderboard | |
| HMMT Nov 2025 | 89.8% | #16 of 28 | Lab model card | |
| MathArena (Apex, IMO, USAMO) | 2.08% | #33 of 47 | Official leaderboard | |
| MathArena Apex Shortlist | 52.1% | #29 of 38 | Official leaderboard | |
| AIME 2026 | 91.7% | #26 of 31 | Official leaderboard | |
| HMMT 2026 | 81.1% | #27 of 31 | Official leaderboard |
Coding
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| LiveCodeBench v6 | 80.7% | #30 of 90 | Lab model card | |
| SWE-bench Verified | 72.4% | #62 of 155 | Lab model card | |
| OJBench | 40.1% | #7 of 16 | Lab model card | |
| Codeforces rating | 1,899 | #31 of 47 | Lab model card | |
| FullStackBench | 58.8% | #6 of 8 | Lab model card | |
| WebDev Arena | 1,357 | #80 of 105 | arena.ai, via Epoch AI | |
| Code Arena | 1,357 | #101 of 128 | Official leaderboard | |
| ALE-Bench | 882 | #116 of 126 | Official leaderboard | |
| FeatureBench | 34.8% | #15 of 16 | Official leaderboard | |
| FeatureBench Lite | 34.8% | #15 of 16 | Official leaderboard |
Agents and tools
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| SnakeBench | 31 | #31 of 188 | Official leaderboard | |
| BFCL V4 | 68.5% | #10 of 30 | Lab model card | |
| VITA-Bench | 41.9% | #6 of 16 | Lab model card | |
| GameWorld | 41.8% | #9 of 22 | Official leaderboard | |
| ScreenSpot-Pro | 70.3% | #14 of 32 | Lab model card | |
| tau2-bench | 79% | #42 of 79 | Lab model card | |
| OpenComputer | 32.3% | #4 of 7 | Official leaderboard | |
| Toolathlon | 31.5% | #30 of 50 | Official leaderboard | |
| AndroidWorld | 64.2% | #15 of 23 | Lab model card | |
| BrowseComp-ZH | 62.1% | #13 of 19 | Lab model card | |
| BrowseComp | 61% | #56 of 81 | Lab model card | |
| Terminal-Bench 2.0 | 41.6% | #49 of 63 | Lab model card | |
| ScienceBoard | 5.92% | #12 of 15 | Official leaderboard | |
| DeepPlanning | 22.6% | #8 of 10 | Lab model card | |
| OSWorld-Verified | 56.2% | #33 of 41 | Lab model card | |
| LiveClawBench | 31.6% | #17 of 17 | Official leaderboard |
Professional work
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| MedXpertQA-MM | 62.4% | #7 of 21 | Lab model card | |
| LMBuild | 55.3% | #6 of 18 | Official leaderboard | |
| SLAKE | 80% | #4 of 10 | Lab model card | |
| PMC-VQA | 62.4% | #5 of 10 | Lab model card | |
| MMEnterprise-Bench | 50.3% | #5 of 9 | Official leaderboard | |
| Vending-Bench 2 | $202 | #59 of 67 | Official leaderboard |
Vision, audio and robotics
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| CountBench | 97.8% | #1 of 28 | Lab model card | |
| RefAdv-S | 67.3% | #1 of 19 | Official leaderboard | |
| MathVista | 87.8% | #5 of 70 | Lab model card | |
| DynaMath | 87.7% | #2 of 23 | Lab model card | |
| MMMU | 82.3% | #11 of 103 | Lab model card | |
| GSM8K-V | 39.9% | #4 of 24 | Official leaderboard | |
| MMBench-EN v1.1 | 92.6% | #5 of 23 | Lab model card | |
| MMStar | 81% | #8 of 36 | Lab model card | |
| ZeroBench | 36.2% | #7 of 31 | Lab model card | |
| OCRBench | 89.4% | #8 of 34 | Lab model card | |
| EmbSpatialBench | 84.5% | #4 of 16 | Lab model card | |
| VideoMME v2 (with subtitles) | 31.4% | #8 of 31 | Official leaderboard | |
| MMLongBench-Doc | 60.2% | #5 of 19 | Lab model card | |
| OVO-S-Bench | 51.7% | #4 of 15 | Official leaderboard | |
| AI2D | 92.9% | #14 of 52 | Lab model card | |
| Video-MME | 87% | #14 of 51 | Lab model card | |
| VLMs Are Blind | 96.9% | #4 of 14 | Lab model card | |
| LingoQA | 82% | #3 of 10 | Lab model card | |
| MATH-Vision (MathVision) | 86% | #16 of 51 | Lab model card | |
| Hypersim | 13.0 | #3 of 9 | Lab model card | |
| TIR-Bench | 59.8% | #2 of 6 | Lab model card | |
| MMVU | 73.3% | #9 of 26 | Lab model card | |
| V* | 93.7% | #6 of 17 | Lab model card | |
| RefSpatial-Bench | 67.7% | #6 of 16 | Lab model card | |
| Nuscene | 15.2 | #3 of 8 | Lab model card | |
| RealWorldQA | 83.7% | #15 of 38 | Lab model card | |
| MLVU | 85.9% | #9 of 22 | Lab model card | |
| RefCOCO / RefCOCO+ / RefCOCOg | 90.9% | #12 of 29 | Lab model card | |
| GeoGuesser environment (FineEnvs) | 0.33 | #6 of 14 | Official leaderboard | |
| SUNRGBD | 35.4 | #4 of 9 | Lab model card | |
| MMMU-Pro | 75% | #41 of 90 | Lab model card | |
| MVBench | 74.6% | #11 of 23 | Lab model card | |
| LVBench | 73.6% | #15 of 31 | Lab model card | |
| Vision Arena | 1,216 | #67 of 136 | Official leaderboard | |
| Video-MMMU | 82.3% | #18 of 36 | Lab model card | |
| CharXiv | 79.5% | #38 of 75 | Lab model card | |
| ERQA | 60.5% | #19 of 36 | Lab model card | |
| CC-OCR | 81% | #8 of 14 | Lab model card | |
| CiteVQA | 17.3% | #11 of 16 | Official leaderboard | |
| BabyVision | 44.6% | #18 of 26 | Lab model card | |
| ODinW-13 | 41.1% | #11 of 13 | Lab model card | |
| BVB | 50.7 | #45 of 45 | Official leaderboard |
Safety and security
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| nocot-bench (NCRI) | 66.6 | #114 of 185 | Official leaderboard |
Other
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| Conceptual Reasoning Index | 46.6 | #80 of 151 | Official leaderboard | |
| LMCA | 34% | #82 of 147 | Official leaderboard | |
| ACCoRD | 60.5 | #90 of 152 | Official leaderboard |
Its lab's numbers put it at 146.0, number 122 of 404
The Self-Reported Index fits one score to the 68 capability results Qwen reported for this model, on the scale of the Epoch Capabilities Index. Labs choose which benchmarks to show and how to run them, so read it as the lab's claim, not an independent measurement. The 90% interval runs from 145.0 to 147.1. How we compute it.
- CountBench 97.8
- VLMs Are Blind 96.9
- IFEval 95
- V* 93.7
- MMLU-Redux 93.2
- AI2D 92.9
- MMBench-EN v1.1 92.6
- HMMT 2025 92
- RefCOCO / RefCOCO+ / RefCOCOg 90.9
- C-Eval 90.5
- HMMT Nov 2025 89.8
- OCRBench 89.4
- MAXIFE 88
- MathVista 87.8
- DynaMath 87.7
- Global PIQA 87.5
- Video-MME 87
- MMLU-Pro 86.1
- MATH-Vision (MathVision) 86
- MMMLU 85.9
- MLVU 85.9
- GPQA Diamond 85.5
- EmbSpatialBench 84.5
- RealWorldQA 83.7
- MMMU 82.3
- Video-MMMU 82.3
- MMLU-ProX 82.2
- LingoQA 82
- INCLUDE 81.6
- MMStar 81
- CC-OCR 81
- LiveCodeBench v6 80.7
- SLAKE 80
- CharXiv 79.5
- tau2-bench 79
- IFBench 76.5
- MMMU-Pro 75
- MVBench 74.6
- LVBench 73.6
- MMVU 73.3
- SWE-bench Verified 72.4
- PolyMath 71.2
- ScreenSpot-Pro 70.3
- HallusionBench 70
- BFCL V4 68.5
- AA-LCR (Artificial Analysis Long Context Reasoning) 66.1
- SuperGPQA 65.6
- AndroidWorld 64.2
- PMC-VQA 62.4
- MedXpertQA-MM 62.4
- BrowseComp-ZH 62.1
- WideSearch 61.1
- BrowseComp 61
- MultiChallenge 60.8
- LongBench v2 60.6
- MMLongBench-Doc 60.2
- FullStackBench 58.8
- NOVA-63 58.1
- OSWorld-Verified 56.2
- SimpleVQA 56
- Humanity's Last Exam 48.5
- BabyVision 44.6
- VITA-Bench 41.9
- Terminal-Bench 2.0 41.6
- ODinW-13 41.1
- OJBench 40.1
- ZeroBench 36.2
- DeepPlanning 22.6
Its lab's numbers next to 3 leaderboards
Where the benchmark's own leaderboard, or Epoch AI's run, also has this model. Gaps mostly come from different harnesses, effort levels and task subsets. Every pair.
| Benchmark | Lab says | Board says | Gap |
|---|---|---|---|
| Global PIQA | 87.5% Global PIQA | 78.5% Leaderboard, exact_match,strict_match; instruct | +9.0 pts |
| MATH-Vision (MathVision) | 86% MathVision | 86% Leaderboard | Same |
| MMLU-Pro | 86.1% MMLU-Pro | 86.1% Leaderboard | Same |
Its launch post
The benchmarks the lab chose to headline, with the scores it gave.