Model comparison
GPT-5.1-Codex vs Mistral Small 3
GPT-5.1-Codex is the stronger model overall, scoring 38.6 to 31.2 on the Noometry Index. Mistral Small 3 costs 60× less per token, which makes it the better buy when GPT-5.1-Codex's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
Mistral AISummary
- The widest gap is in math, where GPT-5.1-Codex leads 30.3 to 16.3.
- Mistral Small 3 is cheaper at $0.05 / $0.08 per million input/output tokens, against $1.25 / $10 for GPT-5.1-Codex.
- GPT-5.1-Codex accepts more context: 400K tokens versus 33K.
- Mistral Small 3 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.1-Codex | Mistral Small 3 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 38.6 | 31.2 |
| Released | 2025-11-12 | 2025-01-30 |
| Weights | Proprietary | Open |
| Context window | 400K | 33K |
| Max output | 128K | 16K |
| Input $ / M tokens | $1.25 | $0.05 |
| Output $ / M tokens | $10 | $0.08 |
| 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 Small 3: 36.5 (#207)
| Benchmark | GPT-5.1-Codex | Mistral Small 3 |
|---|---|---|
| SWE-bench Verified (bash only) | 66% | — |
| LMArena WebDev | 1337 | — |
| BigCodeBench Instruct | — | 45.3% |
| LMArena Coding | — | 1246 |
| BigCodeBench Complete | — | 50.4% |
| ALE-Bench | 1,245 | — |
Agentic & Tool Use Not comparable
GPT-5.1-Codex: 38.0 (#33), Mistral Small 3: —
| Benchmark | GPT-5.1-Codex | Mistral Small 3 |
|---|---|---|
| Terminal-Bench | 60.4% | — |
| METR Time Horizons | 70.8% | — |
Reasoning Not comparable
GPT-5.1-Codex: —, Mistral Small 3: 18.9 (#273)
| Benchmark | GPT-5.1-Codex | Mistral Small 3 |
|---|---|---|
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | — | 1233 |
| Epoch Capabilities Index | — | 127.07 |
Math GPT-5.1-Codex leads
GPT-5.1-Codex: 30.3 (#235), Mistral Small 3: 16.3 (#295)
| Benchmark | GPT-5.1-Codex | Mistral Small 3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 6.7% |
| ProofBench | 9% | — |
| LMArena Math | — | 1240 |
Knowledge Not comparable
GPT-5.1-Codex: —, Mistral Small 3: 25.1 (#263)
| Benchmark | GPT-5.1-Codex | Mistral Small 3 |
|---|---|---|
| GPQA Diamond | — | 47.3% |
| Confabulations | — | 25.2% |
| LMArena Expert | — | 1202 |
Multilingual Not comparable
GPT-5.1-Codex: —, Mistral Small 3: 37.3 (#236)
| Benchmark | GPT-5.1-Codex | Mistral Small 3 |
|---|---|---|
| LMArena Non-English | — | 1198 |
| LMArena Chinese | — | 1204 |
| LMArena French | — | 1203 |
| LMArena German | — | 1211 |
| LMArena Japanese | — | 1111 |
| LMArena Korean | — | 1188 |
| LMArena Russian | — | 1216 |
Instruction Following Not comparable
GPT-5.1-Codex: —, Mistral Small 3: 63.7 (#229)
| Benchmark | GPT-5.1-Codex | Mistral Small 3 |
|---|---|---|
| LMArena Instruction Following | — | 1214 |
Long Context Not comparable
GPT-5.1-Codex: —, Mistral Small 3: 37.8 (#211)
| Benchmark | GPT-5.1-Codex | Mistral Small 3 |
|---|---|---|
| LMArena Longer Query | — | 1246 |
Writing & Preference Not comparable
GPT-5.1-Codex: —, Mistral Small 3: 32.2 (#280)
| Benchmark | GPT-5.1-Codex | Mistral Small 3 |
|---|---|---|
| LMArena Text | — | 1234 |
| LMArena Creative Writing | — | 1195 |
| EQ-Bench Creative Writing | — | 707 |
| LMArena Multi-Turn | — | 1217 |
Frequently asked questions
Is GPT-5.1-Codex better than Mistral Small 3?
GPT-5.1-Codex is the stronger model overall, scoring 38.6 to 31.2 on the Noometry Index. Mistral Small 3 costs 60× less per token, which makes it the better buy when GPT-5.1-Codex's lead doesn't matter for your workload.
Which is cheaper, GPT-5.1-Codex or Mistral Small 3?
Mistral Small 3 is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; GPT-5.1-Codex lists at $1.25 and $10.
Is GPT-5.1-Codex or Mistral Small 3 better for coding?
GPT-5.1-Codex scores higher on coding benchmarks: 41.9 versus 36.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5.1-Codex does, with 400K tokens against 33K.
How many benchmarks do GPT-5.1-Codex and Mistral Small 3 share?
0 benchmarks have published results for both models. GPT-5.1-Codex has 6 scored results on Noometry and Mistral Small 3 has 24.