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GPT-5.2 Chat (2026-02-10)
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GPT-5.2 Chat (2026-02-10) is a closed-weights language model from OpenAI, released February 2026.
Catalogue identity notes
Comparison-only. Arena entry 'gpt-5.2-chat-latest-20260210' (text, vision). Released 2026-02: OpenAI API changelog, Feb 10 (2026): 'Updated the gpt-5.2-chat-latest slug to point to the latest model currently used in ChatGPT'. The Arena entry pins the 2026-02-10 state of the gpt-5.2-chat-latest alias (GPT-5.2 model used in ChatGPT); distinct from gpt-5-2 (reasoning). Shut down 2026-08-10.
$ how it compares
The LLMs ranked either side of GPT-5.2 Chat (2026-02-10), out of 1132 with a score, then more from OpenAI.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 47 |  Grok 4.7 | 75±1 | api $3.00/M | ||
| 48 |  Claude Opus 4.6 | 75±1 | api $10.00/M | ||
| 49 | GPT-5.2 Chat (2026-02-10) | 74±3 | comparison only | ||
| 50 | GPT-5.3-Codex | 74±1 | api $4.81/M | ||
| 51 |  DeepSeek V4 Flash (0731) | 74±1 | api $0.11/M +local | ||
| more from OpenAI | |||||
| 1 | GPT-6 Astra | 87±1 | api $20.00/M | ||
| 3 | GPT-6.1 Sol | 85±1 | api $4.00/M | ||
| 7 | GPT-6 Sol | 83±1 | api $4.00/M | ||
$ what it's good at
chat & writing▁▁▁▃▅▅▆█▆▆▆▂ #28 of 579 * · 57% of its score · 1 test
Beats Claude Sonnet 5.5, GPT-6 Sol, GPT-5.6 Terra here, though they rank higher overall. Trails GLM-5.2, Gemini 3.6 Flash, Gemini 3.5 Flash here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LMArena (text) | 1475.7 ✎ | ▁▁▁▂▃▃▃▆▆▇█▃ beats 352/379 | 57% |
vision & documents▁▁▃▃▂▃▅▅▇▇█▃ #31 of 199 * · 40% of its score · 1 test
Beats Claude Sonnet 5.5, MiMo-V2.6-Pro, GPT-5.6 Terra here, though they rank higher overall. Trails Qwen3.7 Plus, Gemini 3.6 Flash, Gemini 3.5 Flash here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Arena vision (style controlled) | 1278.0 ✎ | ▁▁▂▂▂▂▄▅▅▆██ beats 121/145 | 40% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · LMArena leaderboard dataset 97%
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 | 2 | 97% |
| prior · pull toward the middle | 3% | |
| weighted average | = 74.4 |
$ 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