Model comparison
GPT-4 Turbo vs Mistral Small 3.1
Mistral Small 3.1 is the stronger model overall, scoring 31.7 to 30.5 on the Noometry Index.
Last verified . 22 shared benchmarks.
Mistral AISummary
- They share 22 benchmarks with published results for both. GPT-4 Turbo scores higher in 3 categories and Mistral Small 3.1 in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-4 Turbo leads 47.7 to 37.0.
- The biggest single-benchmark swing is Chess Puzzles: 6% for GPT-4 Turbo and 1% for Mistral Small 3.1.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $10 / $30 for GPT-4 Turbo.
- Mistral Small 3.1 has downloadable open weights; the other is API-only.
Side by side
| GPT-4 Turbo | Mistral Small 3.1 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 30.5 | 31.7 |
| Released | 2023-11-06 | 2025-03-17 |
| Weights | Proprietary | Open |
| Context window | 128K | 128K |
| Max output | 4K | 102K |
| Input $ / M tokens | $10 | $0.35 |
| Output $ / M tokens | $30 | $0.56 |
| Results tracked | 36 | 28 |
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Category by category
Coding Mistral Small 3.1 leads
GPT-4 Turbo: 33.8 (#249), Mistral Small 3.1: 38.3 (#179)
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1268 | 1309 |
| WeirdML | 18% | — |
| BigCodeBench Instruct | 48.2% | — |
| BigCodeBench Complete | 58.2% | — |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73.3% | — |
Agentic & Tool Use Not comparable
GPT-4 Turbo: —, Mistral Small 3.1: —
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 |
|---|---|---|
| METR Time Horizons | 36.7% | — |
Reasoning Mistral Small 3.1 leads
GPT-4 Turbo: 15.3 (#317), Mistral Small 3.1: 19.7 (#254)
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 |
|---|---|---|
| Chess Puzzles | 6% | 1% |
| LMArena Hard Prompts | 1251 | 1278 |
| Epoch Capabilities Index | 127.25 | 127.48 |
| SimpleBench | 25.1% | — |
| DTBench | 61.6% | — |
| LMCA | 9.8% | — |
| ForecastBench | 59.4 | — |
Math Mistral Small 3.1 leads
GPT-4 Turbo: 9.0 (#322), Mistral Small 3.1: 14.7 (#301)
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 6.7% | 3.9% |
| LMArena Math | 1272 | 1262 |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| Omni-MATH | — | 24.8% |
| MATH Level 5 | 46.7% | — |
Knowledge GPT-4 Turbo leads
GPT-4 Turbo: 24.3 (#268), Mistral Small 3.1: 22.6 (#271)
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | 46.6% | 41.9% |
| LMArena Expert | 1223 | 1257 |
| MMLU-Pro | — | 61% |
| Confabulations | 28.4% | — |
| GPQA (HELM) | — | 39.2% |
| MMLU | 81.3% | — |
Multimodal Mistral Small 3.1 leads
GPT-4 Turbo: 30.6 (#110), Mistral Small 3.1: 33.2 (#99)
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | 1090 | 1136 |
Multilingual Too close to call
GPT-4 Turbo: 40.5 (#216), Mistral Small 3.1: 41.2 (#209)
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1245 | 1255 |
| LMArena Chinese | 1242 | 1253 |
| LMArena French | 1276 | 1273 |
| LMArena German | 1259 | 1266 |
| LMArena Japanese | 1194 | 1208 |
| LMArena Korean | 1187 | 1206 |
| LMArena Russian | 1259 | 1263 |
| LMArena Spanish | 1260 | 1283 |
Instruction Following GPT-4 Turbo leads
GPT-4 Turbo: 65.8 (#216), Mistral Small 3.1: 63.6 (#230)
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 |
|---|---|---|
| LMArena Instruction Following | 1249 | 1264 |
| IFEval | — | 75% |
Long Context Mistral Small 3.1 leads
GPT-4 Turbo: 38.0 (#206), Mistral Small 3.1: 39.5 (#178)
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1254 | 1299 |
Writing & Preference GPT-4 Turbo leads
GPT-4 Turbo: 47.7 (#206), Mistral Small 3.1: 37.0 (#259)
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1272 | 1277 |
| LMArena Creative Writing | 1269 | 1253 |
| LMArena Multi-Turn | 1267 | 1270 |
| EQ-Bench Creative Writing | — | 761 |
| WildBench | — | 78.8% |
Frequently asked questions
Is GPT-4 Turbo better than Mistral Small 3.1?
Mistral Small 3.1 is the stronger model overall, scoring 31.7 to 30.5 on the Noometry Index.
Which is cheaper, GPT-4 Turbo or Mistral Small 3.1?
Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; GPT-4 Turbo lists at $10 and $30.
Is GPT-4 Turbo or Mistral Small 3.1 better for coding?
Mistral Small 3.1 scores higher on coding benchmarks: 38.3 versus 33.8 in the Noometry coding category.
Which has the bigger context window?
Both accept 128K tokens.
How many benchmarks do GPT-4 Turbo and Mistral Small 3.1 share?
22 benchmarks have published results for both models. GPT-4 Turbo has 36 scored results on Noometry and Mistral Small 3.1 has 28.