LabsAlibaba / Qwen
Alibaba / Qwen
Track Alibaba / Qwen model scores across public AI benchmarks including GDPval-AA, SuperGPQA, LMArena, GPQA Diamond, and AAII. Each result is shown one benchmark at a time, with source links and evaluation dates — no blended score or composite ranking. 9 models tracked, spanning Qwen and Qwen3.5.
Models 9
Qwen3.7 Max Preview
Qwen · qwen3.7-max-preview
2026-05-14
9 results
Qwen 3.6 27B
Qwen · qwen 3.6 27b
2026-04-22
1 results
Qwen 3.6 Max Preview
Qwen · qwen 3.6 max
2026-04-20
12 results
Qwen 3.6 Plus
Qwen · qwen 3.6 plus
2026-04-02
19 results
Qwen3.5 Max Preview
Qwen · qwen3.5-max-preview
2026-03-25
1 results
Qwen3.5-397B-A17B
Qwen3.5 · qwen/qwen3.5-397b-a17b
2026-02-16
22 results
Qwen3 Max
Qwen · qwen3-max
2025-09-05
15 results
Qwen 3 Coder 480B
Qwen · qwen3-coder-480b
2025-07-22
11 results
Qwen3 235B A22B Instruct 2507
Qwen · qwen3-235b-a22b-instruct-2507
2025-07-21
21 results
Progress by benchmark
Show progress on
Single benchmark only
This view shows GDPval (Elo) only. Other benchmarks use different metrics and are not directly comparable.
Progress matrix
| Model | SWE-bench Verified % resolved | Terminal-Bench 2.1 task success | DeepSWE % resolved | GPQA Diamond accuracy | LiveCodeBench Pro Codeforces Elo | Humanity's Last Exam accuracy | LiveBench score | SWE-bench Pro % resolved | Berkeley Function Calling Leaderboard accuracy | MMMU-Pro accuracy | LMArena source-defined rating | ARC-AGI-1 accuracy | ARC-AGI-2 accuracy | ARC-AGI-3 accuracy | FrontierMath accuracy | AIME (OTIS Mock) accuracy | SimpleQA Verified accuracy | GBA Eval overall score | WeirdML average accuracy | MCP Atlas pass rate | Remote Labor Index automation rate | Artificial Analysis Intelligence Index Index | Epoch Capabilities Index Index | Aider Polyglot % correct | SWE-rebench Resolved rate (pass@1) | MMLU-Pro accuracy | OSWorld task success rate | GAIA: A Benchmark for General AI Assistants accuracy | BrowseComp accuracy | τ²-bench (Telecom) pass^1 | AIME 2026 accuracy | MathVista accuracy | Video-MME accuracy | GDPval Elo | LiveCodeBench Pass@1 | METR Task-Completion Time Horizons 50% time horizon | SciCode accuracy | MMMU (Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark) accuracy | AA-Omniscience: Knowledge and Hallucination Benchmark AA-Omniscience Index | IFBench accuracy | MultiChallenge accuracy | OpenAI-MRCR v2 (Multi-Round Coreference Resolution) accuracy (mean SequenceMatcher similarity) | LongBench v2 accuracy | Global-MMLU accuracy | Video-MMMU accuracy | WebDev Arena Elo | Search Arena Elo | Arena-Hard-Auto v2.0 % win rate | EQ-Bench Creative Writing v3 Elo | Design Arena Elo | AILuminate AI Safety Benchmark Safety grade | MASK (Model Alignment between Statements and Knowledge) Honesty score | MCP-Universe Overall Success Rate | CharXiv accuracy | OCRBench v2 accuracy | ScreenSpot-Pro accuracy | FACTS Grounding Grounding accuracy | BigCodeBench calibrated Pass@1 | SWE-bench Multilingual % resolved | SWE-bench Multimodal % resolved | SuperGPQA accuracy | EnigmaEval accuracy | ZeroBench accuracy | IMO-Bench accuracy | PutnamBench Problems solved | MathArena HMMT February 2026 accuracy | FrontierMath Tier 4 accuracy | Vectara Hallucination Leaderboard Hallucination Rate | Gray Swan Arena (Agent Red-Teaming / Indirect Prompt Injection) Attack Success Rate (ASR) | PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts Difficulty-Weighted Accuracy (DW-ACC) | Vibe Code Bench Overall accuracy | Online-Mind2Web Task success rate | WebArena Task success rate | GSO: Software Optimization Benchmark for SWE-Agents Opt@1 | MultiNRC accuracy | Terminal-Bench 2.0 task success | SWE-Marathon resolution rate (pass@1) | FrontierCode weighted score (Diamond) | FrontierSWE dominance score | ProgramBench almost-resolved rate | CursorBench score | PostTrainBench weighted average score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Qwen3 235B A22B Instruct 2507 Qwen | — | — | — | 80.1% | 1673 | — | — | 21.41% | 52.15% | — | 1419 | — | — | — | 8.48% | 86.7% | 50.1% | — | 38.7% | 12.0% | — | — | 139.1 | 57.3% | — | 82.8% | — | — | — | — | — | — | — | 778 | 52.4% | — | 36.0% | — | — | — | — | — | 58.3% | — | — | — | — | — | — | 1093 | — | — | 18.18% | — | — | — | — | — | — | — | 62.6% | — | — | 53.8% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| Qwen 3 Coder 480B Qwen | — | — | — | — | — | — | — | 38.70% | — | — | — | — | — | — | — | — | — | — | 41.2% | — | — | — | — | 61.8% | — | 78.8% | — | — | — | — | — | — | — | 506 | 58.5% | — | 35.9% | — | — | — | — | — | — | — | — | 1282 | — | — | — | 1197 | — | — | 22.94% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 4.9% | — | — | — | — | — | — | — | — |
| Qwen3 Max Qwen | — | — | — | 72.6% | 1226 | — | — | — | — | — | — | — | — | — | — | 73.3% | 67.5% | — | — | — | — | 31.4 | 144.9 | — | — | 84.1% | — | — | — | — | — | — | — | 1038 | 76.7% | — | 43.1% | — | — | — | — | — | — | 83.3% | — | — | — | — | — | 1165 | — | — | — | — | — | — | — | — | — | — | 65.1% | — | — | — | — | — | — | — | — | — | 3.51% | — | — | — | — | — | — | — | — | — | — | 7.42% |
| Qwen3.5-397B-A17B Qwen3.5 | 76.4% | — | — | 88.4% | — | 28.7% | — | — | 72.9% | 79.0% | — | — | — | — | — | — | — | — | — | — | — | 40.1 | 146.1 | — | — | — | — | — | — | 95.6% | 93.33% | — | — | 1220 | — | — | 42.0% | — | -30 | 78.8% | — | — | — | 90.0% | — | 1393 | — | — | 1469 | 1233 | — | — | — | — | — | 65.6% | — | — | — | — | 70.4% | — | — | — | — | 87.88% | 2.1% | — | — | — | — | — | — | — | — | 52.5% | — | — | — | — | — | — |
| Qwen3.5 Max Preview Qwen | — | — | — | — | — | — | — | — | — | — | 1470 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| Qwen 3.6 Plus Qwen | 57.9% | — | 2.65% | 87.4% | — | — | — | — | — | — | 1437 | — | — | — | 26.21% | 90.6% | 49.1% | — | — | — | — | 50 | 149.1 | — | — | — | — | 37.4% | — | — | — | — | 84.2% | 1354 | — | — | — | — | — | — | — | — | — | — | — | 1460 | — | — | — | 1281 | — | — | — | 81.5% | — | — | — | — | — | — | 71.6% | — | — | — | — | — | 8.3% | — | — | — | 25.57% | — | — | — | — | — | — | — | 22% | — | — | — |
| Qwen 3.6 Max Preview Qwen | 76.7% | — | — | 89.1% | — | — | — | — | — | — | 1444 | — | — | — | 23.1% | 91.1% | 56.9% | — | — | — | — | 51.8 | 150.2 | — | — | — | — | — | — | — | — | — | — | 1504 | — | — | — | — | — | — | — | — | — | — | — | 1486 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 73.9% | — | — | — | — | — | 4.2% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| Qwen 3.6 27B Qwen | — | — | 1.79% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| Qwen3.7 Max Preview Qwen | — | — | — | — | — | — | 74.29% | — | — | — | 1474 | — | — | — | — | — | — | — | — | — | — | 56.6 | — | — | — | — | — | — | — | 94.7% | — | — | — | — | — | — | 48.8% | — | — | 80.5% | — | — | — | — | — | 1541 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 73.6% | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 69.7% | — | — | — | — | — | — |
Scores are not normalised across benchmarks. Each column uses its own metric. Compare columns independently.