Model comparison
GPT-4.1 vs Mistral Small 3.1
GPT-4.1 is the stronger model overall, scoring 35.9 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 8.7× less per token, which makes it the better buy when GPT-4.1's lead doesn't matter for your workload.
Last verified . 28 shared benchmarks.
Mistral AISummary
- They share 28 benchmarks with published results for both. GPT-4.1 scores higher in 7 categories and Mistral Small 3.1 in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-4.1 leads 57.6 to 37.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 38.3% for GPT-4.1 and 3.9% for Mistral Small 3.1.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $2 / $8 for GPT-4.1.
- GPT-4.1 accepts more context: 1.05M tokens versus 128K.
- Mistral Small 3.1 has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 | Mistral Small 3.1 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 35.9 | 31.7 |
| Released | 2025-04-14 | 2025-03-17 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 33K | 102K |
| Input $ / M tokens | $2 | $0.35 |
| Output $ / M tokens | $8 | $0.56 |
| Results tracked | 52 | 28 |
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Category by category
Coding Mistral Small 3.1 leads
GPT-4.1: 34.4 (#238), Mistral Small 3.1: 38.3 (#179)
| Benchmark | GPT-4.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1391 | 1309 |
| SWE-bench Verified | 48.5% | — |
| SWE-bench Verified (bash only) | 39.6% | — |
| Aider Polyglot | 52.4% | — |
| WeirdML | 39% | — |
| CadEval | 42% | — |
| ALE-Bench | 558.1 | — |
Agentic & Tool Use Not comparable
GPT-4.1: 34.7 (#43), Mistral Small 3.1: —
| Benchmark | GPT-4.1 | Mistral Small 3.1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 54% | — |
Reasoning Mistral Small 3.1 leads
GPT-4.1: 11.7 (#339), Mistral Small 3.1: 19.7 (#254)
| Benchmark | GPT-4.1 | Mistral Small 3.1 |
|---|---|---|
| Chess Puzzles | 6% | 1% |
| LMArena Hard Prompts | 1384 | 1278 |
| Epoch Capabilities Index | 136.78 | 127.48 |
| ARC-AGI-2 | 0.4% | — |
| SimpleBench | 27% | — |
| Kagi LLM Benchmark | 52.3% | — |
| ARC-AGI-1 | 5.5% | — |
| EnigmaEval | 2.2% | — |
| DTBench | 68.3% | — |
| LMCA | 25.6% | — |
| ForecastBench | 61.5 | — |
Math GPT-4.1 leads
GPT-4.1: 22.3 (#280), Mistral Small 3.1: 14.7 (#301)
| Benchmark | GPT-4.1 | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 38.3% | 3.9% |
| Omni-MATH | 47.1% | 24.8% |
| LMArena Math | 1370 | 1262 |
| FrontierMath (Tiers 1-3) | 6% | — |
| MATH Level 5 | 83% | — |
| FrontierMath (Feb 2025 set) | 5.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge GPT-4.1 leads
GPT-4.1: 37.1 (#160), Mistral Small 3.1: 22.6 (#271)
| Benchmark | GPT-4.1 | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | 66.9% | 41.9% |
| MMLU-Pro | 81.1% | 61% |
| GPQA (HELM) | 65.9% | 39.2% |
| LMArena Expert | 1364 | 1257 |
| Humanity's Last Exam | 5.4% | — |
| SimpleQA Verified | 31.1% | — |
| Vectara Hallucination Rate | 5.6% | — |
Multimodal GPT-4.1 leads
GPT-4.1: 38.2 (#67), Mistral Small 3.1: 33.2 (#99)
| Benchmark | GPT-4.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | 1211 | 1136 |
| GeoBench | 72% | — |
Multilingual GPT-4.1 leads
GPT-4.1: 49.4 (#133), Mistral Small 3.1: 41.2 (#209)
| Benchmark | GPT-4.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1370 | 1255 |
| LMArena Chinese | 1382 | 1253 |
| LMArena French | 1382 | 1273 |
| LMArena German | 1381 | 1266 |
| LMArena Japanese | 1319 | 1208 |
| LMArena Korean | 1339 | 1206 |
| LMArena Russian | 1377 | 1263 |
| LMArena Spanish | 1376 | 1283 |
Instruction Following GPT-4.1 leads
GPT-4.1: 71.3 (#153), Mistral Small 3.1: 63.6 (#230)
| Benchmark | GPT-4.1 | Mistral Small 3.1 |
|---|---|---|
| IFEval | 83.8% | 75% |
| LMArena Instruction Following | 1367 | 1264 |
Long Context Too close to call
GPT-4.1: 40.0 (#163), Mistral Small 3.1: 39.5 (#178)
| Benchmark | GPT-4.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1385 | 1299 |
| Fiction.LiveBench | 63.9% | — |
Writing & Preference GPT-4.1 leads
GPT-4.1: 57.6 (#125), Mistral Small 3.1: 37.0 (#259)
| Benchmark | GPT-4.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1383 | 1277 |
| LMArena Creative Writing | 1363 | 1253 |
| EQ-Bench Creative Writing | 1420 | 761 |
| WildBench | 85.4% | 78.8% |
| LMArena Multi-Turn | 1398 | 1270 |
Frequently asked questions
Is GPT-4.1 better than Mistral Small 3.1?
GPT-4.1 is the stronger model overall, scoring 35.9 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 8.7× less per token, which makes it the better buy when GPT-4.1's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 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-4.1 lists at $2 and $8.
Is GPT-4.1 or Mistral Small 3.1 better for coding?
Mistral Small 3.1 scores higher on coding benchmarks: 38.3 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4.1 and Mistral Small 3.1 share?
28 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and Mistral Small 3.1 has 28.