whatmodel.sh / Qwen-Plus (2024-11-27)
Qwen-Plus (2024-11-27)
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Qwen-Plus (2024-11-27) is a closed-weights language model from Alibaba, released November 2024.
Catalogue identity notes
Comparison-only. Arena entry 'qwen2.5-plus-1127' (text). LMArena's leaderboard table (arena-leaderboard space @6f2eeeb) labels 'qwen2.5-plus-1127' as 'Qwen2.5-plus-1127' (Alibaba, Proprietary), linking https://help.aliyun.com/zh/model-studio/getting-started/models?spm=a2c4g.11186623.0.i7. Released 2024-11: date in Alibaba's snapshot id qwen-plus-2024-11-27. Arena 'qwen2.5-plus-1127' corresponds to Alibaba alias qwen-plus-1127 = snapshot qwen-plus-2024-11-27 (the 'qwen2.5-' prefix is the Arena's label); retired 2026-01-30 (archived Model Studio deprecation page).
$ how it compares
The LLMs ranked either side of Qwen-Plus (2024-11-27), out of 1132 with a score, then more from Alibaba.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 403 |  GPT-4 Turbo (2024-04-09) | 55±0 | api $15.00/M | ||
| 404 |  Yi-Lightning | 55±1 | api price unknown | ||
| 405 | Qwen-Plus (2024-11-27) | 55±3 | comparison only | ||
| 406 | Qwen2.5 72B Instruct | 55±1 | api $0.37/M +local | ||
| 407 |  Mistral Large 2 (2411) | 55±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
chat & writing▁▁▁▃▅▅▆█▆▆▆▂ #284 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, Gemma 3n E4B, LFM2.5 1.2B Thinking here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LMArena (text) | 1314.6 ✎ | ▁▁▁▂▃▃▃▆▆▇█▃ beats 146/379 | 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 | = 55.3 |
$ 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