whatmodel.sh / Qwen-VL-Max (2024-11-19)
Qwen-VL-Max (2024-11-19)
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Qwen-VL-Max (2024-11-19) is a closed-weights language model from Alibaba, released November 2024.
Catalogue identity notes
Comparison-only. Arena entry 'qwen-vl-max-1119' (vision). LMArena's leaderboard table (arena-leaderboard space @6f2eeeb) labels 'qwen-vl-max-1119' as 'Qwen-VL-Max-1119' (Alibaba, Proprietary), linking https://help.aliyun.com/zh/model-studio/user-guide/vision/?spm=a2c4g.11186623.0.0.33d259a8vPlZoe#f1cbd5b8a8k5w. Released 2024-11: date in Alibaba's snapshot id qwen-vl-max-2024-11-19. Arena 'qwen-vl-max-1119' is Alibaba's alias for snapshot qwen-vl-max-2024-11-19 (archived Model Studio help pages); retired.
$ how it compares
The LLMs ranked either side of Qwen-VL-Max (2024-11-19), out of 1132 with a score, then more from Alibaba.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 513 |  ERNIE 4.5 21B-A3B | 52±1 | comparison only | ||
| 514 |  Bielik 11B v2.2 Instruct | 52±3 | local | ||
| 515 | Qwen-VL-Max (2024-11-19) | 52±4 | comparison only | ||
| 516 |  Granite 4.0 H Small (32B-A9B) | 52±1 | api $0.11/M +local | ||
| 517 |  Llama 3.1 Nemotron 70B Instruct | 52±1 | 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
vision & documents▁▁▃▃▂▃▅▅▇▇█▃ #156 of 199 * · 93% of its score · 1 test
Beats DeepSeek V4 Flash Vision (Exp), GPT-4o mini (2024-07-18) here, though they rank higher overall. Trails Qwen3.5 2B here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Arena vision (style controlled) | 1084.7 ✎ | ▁▁▂▂▂▃▄▅▅▆██ beats 26/145 | 93% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · LMArena leaderboard dataset 93%
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 | 93% |
| prior · pull toward the middle | 7% | |
| weighted average | = 51.9 |
$ 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