Alibaba
availableShows if the model has enough results for an index.Qwen 3.6 Max (preview)
Qwen 3.6 Max (preview) is a reasoning model from Alibaba in the Qwen 3.6 Max family. 22 benchmarks count toward its score, in 6 categories.
IndexOverall score. 50 is the middle.58.3 ±4.9
CoverageShare of the index weight with results.85%
SpeedOutput tokens per second.64/s
Input / 1MUS dollars per 1M input tokens.$1.03
Output / 1MUS dollars per 1M output tokens.$6.16
ContextMaximum tokens in one request.262K
EloLMArena rating and rank.1446 (#50)
50 is the middle of the board. The range shows the doubt in the index.
5,186 votes. Elo shows what people prefer. It does not change the score.
CapabilitiesScore per category. 50 is the middle.
50 is the middleResults
22 counted| BenchmarkThe test name. | CategoryThe capability that the test measures. | ResultThe score from the publisher. | IndexThis result on the index scale. | RunThe settings of the run. | DateDate of the result. | Published byThe source of the result. |
|---|---|---|---|---|---|---|
| τ²-Bench Tool-Agent-User Evaluation | Agentic | 95.9% | 67.6 | — | — | Victor Barres et al. |
| OTIS Mock AIME 2024-2025 | Math | 91.1% | 62.5 | — | — | Epoch AI |
| Artificial Analysis GPQA Diamond | Knowledge | 88.8% | 59.6 | — | — | Artificial Analysis |
| GPQA diamond | Knowledge | 87.4% | 58.9 | — | — | Epoch AI |
| Artificial Analysis Long Context Reasoning | Reasoning | 80.7% | 64.1 | — | — | Artificial Analysis |
| SWE-Bench verified | Coding | 76.7% | 59.0 | — | — | Epoch AI |
| Artificial Analysis IFBench | Instruction | 76.6% | 66.8 | — | — | Artificial Analysis |
| SuperGPQA: Scaling LLM Evaluation Across 285 Graduate Disciplines | Knowledge | 73.9% | 58.7 | — | — | Xiaoxuan Du et al. |
| SWE-bench | Coding | 72.8% | 55.9 | — | 1 Sept 2026 | Vals AI |
| QwenClawBench | Agentic | 59.0% | 57.9 | — | — | Qwen |
| SWE-bench Pro | Coding | 57.3% | 59.4 | — | — | Xiang Deng et al. |
| SimpleQA Verified | Knowledge | 52.0% | 69.7 | — | — | Epoch AI |
| Terminal-Bench 2.0 | Agentic | 51.7% | 59.6 | — | 4 Jun 2026 | Vals AI |
| Scientific Code Benchmark | Coding | 47.0% | 57.4 | — | — | Benchmark authors |
| NL2Repo | Coding | 42.9% | 58.6 | — | — | MiniMax |
| Artificial Analysis Omniscience Accuracy | Knowledge | 37.9% | 60.8 | — | — | Artificial Analysis |
| Artificial Analysis Humanity's Last Exam | Knowledge | 30.8% | 58.0 | — | — | Artificial Analysis |
| Artificial Analysis Intelligence Index | Knowledge | 28.4% | 57.9 | — | — | Artificial Analysis |
| FrontierMath-2025-02-28-Private | Math | 23.1% | 52.2 | — | — | Epoch AI |
| Chess Puzzles | Reasoning | 20.0% | 49.4 | — | — | Epoch AI |
| Mystery Game Puzzles | Reasoning | 19.0% | 54.1 | none effort | — | Epoch AI |
| FrontierMath-Tier-4-2025-07-01-Private | Math | 4.2% | 48.0 | — | — | Epoch AI |
| Critical Physics Tasks | Reasoning | 3.7% | 46.1 | — | — | Artificial Analysis |
22 benchmarks count, from 23 of 23 results. A grey row does not count. Too few models took that benchmark.