Alibaba
availableShows if the model has enough results for an index.Qwen3.5-122B-A10B
Qwen3.5-122B-A10B is a reasoning model from Alibaba. 24 benchmarks count toward its score, in 6 categories.
IndexOverall score out of 100.52.3 ±4.8
CoverageShare of the index weight with results.85%
SpeedOutput tokens per second.76/s
Input / 1MUS dollars per 1M input tokens.$0.26
Output / 1MUS dollars per 1M output tokens.$2.08
ContextMaximum tokens in one request.262K
EloLMArena rating and rank.1418 (#113)
The index is a score out of 100. The ± range shows how much it can change.
28,359 votes. Elo shows what people prefer. It does not change the score.
CapabilitiesScore per category, out of 100.
Out of 100Results
24 counted| BenchmarkThe test name. | CategoryThe capability that the test measures. | ResultThe score from the publisher. | IndexThis result as a score out of 100. | RunThe settings of the run. | DateDate of the result. | Published byThe source of the result. |
|---|---|---|---|---|---|---|
| τ²-Bench Tool-Agent-User Evaluation | Agentic | 93.6% | 66.0 | — | — | Victor Barres et al. |
| Instruction-Following Eval | Instruction | 93.4% | 52.5 | — | — | Jeffrey Zhou et al. |
| V* | Multimodal | 93.2% | 53.1 | — | — | Z.AI |
| Massive Multitask Language Understanding Professional | Knowledge | 86.7% | 57.1 | — | — | Yubo Wang et al. |
| Graduate-Level Google-Proof Q&A | Knowledge | 86.6% | 58.2 | — | — | David Rein et al. |
| MathVision | Multimodal | 86.2% | — | — | — | Qwen |
| Artificial Analysis GPQA Diamond | Knowledge | 85.7% | 56.4 | — | — | Artificial Analysis |
| Massive Multi-discipline Multimodal Understanding | Multimodal | 83.9% | 53.1 | — | — | MMMU authors |
| MMLU-ProX | Multilingual | 82.2% | — | — | — | MMLU-ProX authors |
| CharXiv Reasoning | Multimodal | 77.2% | 54.0 | — | — | CharXiv authors |
| Artificial Analysis Long Context Reasoning | Reasoning | 76.3% | 61.0 | — | — | Artificial Analysis |
| Artificial Analysis IFBench | Instruction | 75.7% | 65.9 | — | — | Artificial Analysis |
| Artificial Analysis MMMU-Pro | Multimodal | 75.0% | 58.7 | — | — | Artificial Analysis |
| Multimodal Multi-disciplinary Video Understanding | Multimodal | 74.7% | — | — | — | MMVU benchmark maintainers |
| Software Engineering Benchmark Verified | Coding | 72.0% | 55.3 | — | — | Carlos E. Jimenez et al. |
| SuperGPQA: Scaling LLM Evaluation Across 285 Graduate Disciplines | Knowledge | 67.1% | 53.0 | — | — | Xiaoxuan Du et al. |
| BrowseComp | Agentic | 63.8% | 53.5 | — | — | OpenAI |
| LongBench v2 | Reasoning | 60.2% | — | — | — | LongBench v2 authors |
| OSWorld-Verified | Agentic | 58.0% | 47.7 | — | — | Tianbao Xie et al. |
| Artificial Analysis Coding Index | Coding | 45.7% | 51.2 | — | — | Artificial Analysis |
| Artificial Analysis SciCode | Coding | 39.7% | 48.0 | — | — | Artificial Analysis |
| Artificial Analysis Humanity's Last Exam | Knowledge | 25.2% | 51.9 | — | — | Artificial Analysis |
| Artificial Analysis Omniscience Accuracy | Knowledge | 24.4% | 44.1 | — | — | Artificial Analysis |
| Mystery Game Puzzles | Reasoning | 17.0% | 52.0 | none effort | — | Epoch AI |
| Artificial Analysis Intelligence Index | Knowledge | 15.6% | 41.9 | — | — | Artificial Analysis |
| GDPval-AA normalized | Agentic | 15.1% | 47.2 | — | — | Artificial Analysis |
| Artificial Analysis Agentic Index | Agentic | 9.6% | 45.0 | — | — | Artificial Analysis |
| Critical Physics Tasks | Reasoning | 0.6% | 39.6 | — | — | Artificial Analysis |
24 benchmarks count, from 24 of 28 results. A grey row does not count. Too few models took that benchmark.