Model comparison
GPT-5.1-Codex vs Mistral Large 3
GPT-5.1-Codex and Mistral Large 3 score almost the same on the Noometry Index (38.6 vs 39.1), so choose on price, context window or the category you care about most.
Last verified . 1 shared benchmarks.
Mistral AISummary
- They share 1 benchmark with published results for both. GPT-5.1-Codex scores higher in 1 category and Mistral Large 3 in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in math, where Mistral Large 3 leads 38.7 to 30.3.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $1.25 / $10 for GPT-5.1-Codex.
- GPT-5.1-Codex accepts more context: 400K tokens versus 262K.
- Mistral Large 3 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.1-Codex | Mistral Large 3 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 38.6 | 39.1 |
| Released | 2025-11-12 | 2025-12-02 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 8K |
| Input $ / M tokens | $1.25 | $0.25 |
| Output $ / M tokens | $10 | $0.75 |
| Results tracked | 6 | 24 |
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Category by category
Coding GPT-5.1-Codex leads
GPT-5.1-Codex: 41.9 (#116), Mistral Large 3: 34.4 (#237)
| Benchmark | GPT-5.1-Codex | Mistral Large 3 |
|---|---|---|
| LMArena WebDev | 1337 | 1230 |
| SWE-bench Verified (bash only) | 66% | — |
| LMArena Coding | — | 1448 |
| ALE-Bench | 1,245 | — |
Agentic & Tool Use Not comparable
GPT-5.1-Codex: 38.0 (#33), Mistral Large 3: —
| Benchmark | GPT-5.1-Codex | Mistral Large 3 |
|---|---|---|
| Terminal-Bench | 60.4% | — |
| METR Time Horizons | 70.8% | — |
Reasoning Not comparable
GPT-5.1-Codex: —, Mistral Large 3: 15.2 (#319)
| Benchmark | GPT-5.1-Codex | Mistral Large 3 |
|---|---|---|
| Kagi LLM Benchmark | — | 50.9% |
| NYT Connections (extended) | — | 7.5% |
| Thematic Generalization | — | 23% |
| LMArena Hard Prompts | — | 1429 |
Math Mistral Large 3 leads
GPT-5.1-Codex: 30.3 (#235), Mistral Large 3: 38.7 (#129)
| Benchmark | GPT-5.1-Codex | Mistral Large 3 |
|---|---|---|
| ProofBench | 9% | — |
| LMArena Math | — | 1414 |
Knowledge Not comparable
GPT-5.1-Codex: —, Mistral Large 3: 36.0 (#177)
| Benchmark | GPT-5.1-Codex | Mistral Large 3 |
|---|---|---|
| Vectara Hallucination Rate | — | 14.5% |
| LMArena Expert | — | 1421 |
Multimodal Not comparable
GPT-5.1-Codex: —, Mistral Large 3: 38.2 (#66)
| Benchmark | GPT-5.1-Codex | Mistral Large 3 |
|---|---|---|
| LMArena Vision | — | 1221 |
Multilingual Not comparable
GPT-5.1-Codex: —, Mistral Large 3: 52.5 (#84)
| Benchmark | GPT-5.1-Codex | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | — | 1413 |
| LMArena Chinese | — | 1447 |
| LMArena French | — | 1455 |
| LMArena German | — | 1437 |
| LMArena Japanese | — | 1394 |
| LMArena Korean | — | 1384 |
| LMArena Russian | — | 1411 |
| LMArena Spanish | — | 1440 |
Instruction Following Not comparable
GPT-5.1-Codex: —, Mistral Large 3: 74.0 (#108)
| Benchmark | GPT-5.1-Codex | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | — | 1403 |
Long Context Not comparable
GPT-5.1-Codex: —, Mistral Large 3: 43.1 (#105)
| Benchmark | GPT-5.1-Codex | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | — | 1413 |
Writing & Preference Not comparable
GPT-5.1-Codex: —, Mistral Large 3: 60.0 (#101)
| Benchmark | GPT-5.1-Codex | Mistral Large 3 |
|---|---|---|
| LMArena Text | — | 1428 |
| LMArena Creative Writing | — | 1386 |
| EQ-Bench Creative Writing | — | 1412 |
| LMArena Multi-Turn | — | 1429 |
Frequently asked questions
Is GPT-5.1-Codex better than Mistral Large 3?
GPT-5.1-Codex and Mistral Large 3 score almost the same on the Noometry Index (38.6 vs 39.1), so choose on price, context window or the category you care about most.
Which is cheaper, GPT-5.1-Codex or Mistral Large 3?
Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; GPT-5.1-Codex lists at $1.25 and $10.
Is GPT-5.1-Codex or Mistral Large 3 better for coding?
GPT-5.1-Codex scores higher on coding benchmarks: 41.9 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
GPT-5.1-Codex does, with 400K tokens against 262K.
How many benchmarks do GPT-5.1-Codex and Mistral Large 3 share?
1 benchmark has published results for both models. GPT-5.1-Codex has 6 scored results on Noometry and Mistral Large 3 has 24.