Model comparison
GPT-5.2 Codex vs Mistral
GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 29.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
Mistral AISummary
- The widest gap is in coding, where GPT-5.2 Codex leads 45.5 to 33.8.
Side by side
| GPT-5.2 Codex | Mistral | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 42.6 | 29.9 |
| Released | 2025-12-18 | — |
| Weights | Proprietary | Proprietary |
| Context window | 400K | — |
| Max output | 128K | — |
| Input $ / M tokens | $1.75 | — |
| Output $ / M tokens | $14 | — |
| Results tracked | 5 | 22 |
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Category by category
Coding GPT-5.2 Codex leads
GPT-5.2 Codex: 45.5 (#71), Mistral: 33.8 (#250)
| Benchmark | GPT-5.2 Codex | Mistral |
|---|---|---|
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1339 | — |
| SWE-bench Multilingual | 66.3% | — |
| LMArena Coding | — | 1162 |
| ALE-Bench | 1,300 | — |
Agentic & Tool Use Not comparable
GPT-5.2 Codex: 41.0 (#22), Mistral: —
| Benchmark | GPT-5.2 Codex | Mistral |
|---|---|---|
| Terminal-Bench | 66.5% | — |
Reasoning Not comparable
GPT-5.2 Codex: —, Mistral: 22.2 (#200)
| Benchmark | GPT-5.2 Codex | Mistral |
|---|---|---|
| LMArena Hard Prompts | — | 1149 |
Math Not comparable
GPT-5.2 Codex: —, Mistral: 22.3 (#278)
| Benchmark | GPT-5.2 Codex | Mistral |
|---|---|---|
| Omni-MATH | — | 7.2% |
| LMArena Math | — | 1180 |
Knowledge Not comparable
GPT-5.2 Codex: —, Mistral: 16.6 (#288)
| Benchmark | GPT-5.2 Codex | Mistral |
|---|---|---|
| MMLU-Pro | — | 27.7% |
| GPQA (HELM) | — | 30.3% |
| LMArena Expert | — | 1125 |
Multilingual Not comparable
GPT-5.2 Codex: —, Mistral: 32.8 (#254)
| Benchmark | GPT-5.2 Codex | Mistral |
|---|---|---|
| LMArena Non-English | — | 1129 |
| LMArena Chinese | — | 1109 |
| LMArena French | — | 1180 |
| LMArena German | — | 1155 |
| LMArena Japanese | — | 1013 |
| LMArena Korean | — | 1032 |
| LMArena Russian | — | 1168 |
| LMArena Spanish | — | 1143 |
Instruction Following Not comparable
GPT-5.2 Codex: —, Mistral: 52.6 (#288)
| Benchmark | GPT-5.2 Codex | Mistral |
|---|---|---|
| IFEval | — | 56.8% |
| LMArena Instruction Following | — | 1152 |
Long Context Not comparable
GPT-5.2 Codex: —, Mistral: 35.0 (#245)
| Benchmark | GPT-5.2 Codex | Mistral |
|---|---|---|
| LMArena Longer Query | — | 1153 |
Writing & Preference Not comparable
GPT-5.2 Codex: —, Mistral: 37.0 (#260)
| Benchmark | GPT-5.2 Codex | Mistral |
|---|---|---|
| LMArena Text | — | 1165 |
| LMArena Creative Writing | — | 1158 |
| WildBench | — | 66% |
| LMArena Multi-Turn | — | 1147 |
Frequently asked questions
Is GPT-5.2 Codex better than Mistral?
GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 29.9 on the Noometry Index.
Is GPT-5.2 Codex or Mistral better for coding?
GPT-5.2 Codex scores higher on coding benchmarks: 45.5 versus 33.8 in the Noometry coding category.
How many benchmarks do GPT-5.2 Codex and Mistral share?
0 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Mistral has 22.