Model comparison
GPT-4.1 vs Mistral
GPT-4.1 is the stronger model overall, scoring 35.9 to 29.9 on the Noometry Index.
Last verified . 22 shared benchmarks.
Mistral AISummary
- They share 22 benchmarks with published results for both. GPT-4.1 scores higher in 6 categories and Mistral in 2 categories; 6 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 MMLU-Pro: 81.1% for GPT-4.1 and 27.7% for Mistral.
Side by side
| GPT-4.1 | Mistral | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 35.9 | 29.9 |
| Released | 2025-04-14 | — |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | — |
| Max output | 33K | — |
| Input $ / M tokens | $2 | — |
| Output $ / M tokens | $8 | — |
| Results tracked | 52 | 22 |
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Category by category
Coding Too close to call
GPT-4.1: 34.4 (#238), Mistral: 33.8 (#250)
| Benchmark | GPT-4.1 | Mistral |
|---|---|---|
| LMArena Coding | 1391 | 1162 |
| 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: —
| Benchmark | GPT-4.1 | Mistral |
|---|---|---|
| Berkeley Function Calling Leaderboard | 54% | — |
Reasoning Mistral leads
GPT-4.1: 11.7 (#339), Mistral: 22.2 (#200)
| Benchmark | GPT-4.1 | Mistral |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1149 |
| ARC-AGI-2 | 0.4% | — |
| SimpleBench | 27% | — |
| Kagi LLM Benchmark | 52.3% | — |
| ARC-AGI-1 | 5.5% | — |
| Chess Puzzles | 6% | — |
| EnigmaEval | 2.2% | — |
| DTBench | 68.3% | — |
| LMCA | 25.6% | — |
| Epoch Capabilities Index | 136.78 | — |
| ForecastBench | 61.5 | — |
Math Too close to call
GPT-4.1: 22.3 (#280), Mistral: 22.3 (#278)
| Benchmark | GPT-4.1 | Mistral |
|---|---|---|
| Omni-MATH | 47.1% | 7.2% |
| LMArena Math | 1370 | 1180 |
| FrontierMath (Tiers 1-3) | 6% | — |
| OTIS Mock AIME 2024-2025 | 38.3% | — |
| 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: 16.6 (#288)
| Benchmark | GPT-4.1 | Mistral |
|---|---|---|
| MMLU-Pro | 81.1% | 27.7% |
| GPQA (HELM) | 65.9% | 30.3% |
| LMArena Expert | 1364 | 1125 |
| GPQA Diamond | 66.9% | — |
| Humanity's Last Exam | 5.4% | — |
| SimpleQA Verified | 31.1% | — |
| Vectara Hallucination Rate | 5.6% | — |
Multimodal Not comparable
GPT-4.1: 38.2 (#67), Mistral: —
| Benchmark | GPT-4.1 | Mistral |
|---|---|---|
| LMArena Vision | 1211 | — |
| GeoBench | 72% | — |
Multilingual GPT-4.1 leads
GPT-4.1: 49.4 (#133), Mistral: 32.8 (#254)
| Benchmark | GPT-4.1 | Mistral |
|---|---|---|
| LMArena Non-English | 1370 | 1129 |
| LMArena Chinese | 1382 | 1109 |
| LMArena French | 1382 | 1180 |
| LMArena German | 1381 | 1155 |
| LMArena Japanese | 1319 | 1013 |
| LMArena Korean | 1339 | 1032 |
| LMArena Russian | 1377 | 1168 |
| LMArena Spanish | 1376 | 1143 |
Instruction Following GPT-4.1 leads
GPT-4.1: 71.3 (#153), Mistral: 52.6 (#288)
| Benchmark | GPT-4.1 | Mistral |
|---|---|---|
| IFEval | 83.8% | 56.8% |
| LMArena Instruction Following | 1367 | 1152 |
Long Context GPT-4.1 leads
GPT-4.1: 40.0 (#163), Mistral: 35.0 (#245)
| Benchmark | GPT-4.1 | Mistral |
|---|---|---|
| LMArena Longer Query | 1385 | 1153 |
| Fiction.LiveBench | 63.9% | — |
Writing & Preference GPT-4.1 leads
GPT-4.1: 57.6 (#125), Mistral: 37.0 (#260)
| Benchmark | GPT-4.1 | Mistral |
|---|---|---|
| LMArena Text | 1383 | 1165 |
| LMArena Creative Writing | 1363 | 1158 |
| WildBench | 85.4% | 66% |
| LMArena Multi-Turn | 1398 | 1147 |
| EQ-Bench Creative Writing | 1420 | — |
Frequently asked questions
Is GPT-4.1 better than Mistral?
GPT-4.1 is the stronger model overall, scoring 35.9 to 29.9 on the Noometry Index.
Is GPT-4.1 or Mistral better for coding?
They score almost the same on coding (34.4 vs 33.8); test both on your own repository before choosing.
How many benchmarks do GPT-4.1 and Mistral share?
22 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and Mistral has 22.