whatmodel.sh / Qwen-Max (2024-09-19)
Qwen-Max (2024-09-19)
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Qwen-Max (2024-09-19) is a closed-weights language model from Alibaba, released September 2024.
Catalogue identity notes
Comparison-only. Arena entry 'qwen-max-0919' (text). LMArena's leaderboard table (arena-leaderboard space @6f2eeeb) labels 'qwen-max-0919' as 'Qwen-Max-0919' (Alibaba, Qwen), linking https://help.aliyun.com/zh/dashscope/developer-reference/model-introduction. Released 2024-09: date in Alibaba's snapshot id qwen-max-2024-09-19. Arena 'qwen-max-0919' is Alibaba's own short alias for snapshot qwen-max-2024-09-19 (archived Model Studio help pages); retired.
$ how it compares
The LLMs ranked either side of Qwen-Max (2024-09-19), out of 1132 with a score, then more from Alibaba.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 393 |  Nemotron Nano 9B v2 | 56±1 | api $0.10/M +local | ||
| 394 |  Grok 2 (2024-08-13) | 56±3 | comparison only | ||
| 395 | Qwen-Max (2024-09-19) | 56±3 | comparison only | ||
| 396 |  Hunyuan-Large-Vision | 56±3 | comparison only | ||
| 397 |  K2-Think | 56±4 | local | ||
| more from Alibaba | |||||
| 18 | Qwen3.8 Max (2.4T-A95B) | 78±1 | api $3.00/M +local | ||
| 34 | Qwen3.8 Max (0902) | 76±1 | api $3.00/M | ||
| 37 | Qwen3.8-Flash-Next | 75±1 | local | ||
$ what it's good at
chat & writing▁▁▁▃▅▅▆█▆▆▆▂ #277 of 579 * · 95% of its score · 1 test
Beats Granite 4.2 8B, Qwen3-VL 30B-A3B Thinking, Mistral Small 4 (119B-A6.5B) here, though they rank higher overall. Trails LFM2.5 1.2B Instruct, LFM2.5 1.2B Thinking, Gemma 3 12B here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LMArena (text) | 1318.1 ✎ | ▁▁▁▂▃▃▃▆▆▇█▃ beats 151/379 | 95% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · LMArena leaderboard dataset 95%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
 LMArena leaderboard dataset | 1 | 95% |
| prior · pull toward the middle | 5% | |
| weighted average | = 55.7 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json