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GPT-5-Codex
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GPT-5-Codex is a closed-weights language model from OpenAI, released September 2025.
Catalogue identity notes
Comparison-only, proposed so the WebApp1K-Duo entry 'gpt-5-codex' (webapp1k-duo-react-pass1, 43 catalogue models) counts. Released 2025-09: OpenAI API changelog, Sep 23 (2025): 'Launched special-purpose model gpt-5-codex, built and optimized for use with the Codex CLI'. Undated API alias (no dated snapshot listed). OpenAI deprecations page: gpt-5-codex shut down July 23, 2026 (replacement gpt-5.6-sol). Distinct from gpt-5-1-codex and gpt-5.
$ how it compares
The LLMs ranked either side of GPT-5-Codex, out of 1132 with a score, then more from OpenAI.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 138 |  Ornith 1.0 35B (35B-A3B) | 68±1 | local | ||
| 139 |  Hy3 preview (295B-A21B) | 68±1 | local | ||
| 140 | GPT-5-Codex | 68±5 | comparison only | ||
| 141 | GPT-5 mini | 67±1 | api $0.69/M | ||
| 142 |  Gemini 2.5 Pro | 67±1 | api $3.44/M | ||
| 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
coding▁▁▁▃▅▇█▇▅▄▂▁ #111 of 549 * · 90% of its score · 1 test
Beats Grok 4.20 (0309 reasoning), Grok 4.3, Muse Glimmer 30B here, though they rank higher overall. Trails Llama 3.1 Nemotron Ultra 253B v1, Nemotron Cascade 2 30B-A3B, MiniMax-M2.1 here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| WebApp1K-Duo-React pass@1 (onekq-ai) | 75.0% ✎ | ▁··▁·▁▁▁▆█▇█ beats 36/45 | 90% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · WebApp1K models leaderboard (… 90%
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 |
|---|---|---|
 WebApp1K models leaderboard (onekq-ai) | 1 | 90% |
| prior · pull toward the middle | 10% | |
| weighted average | = 67.6 |
$ 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