Model comparison
GPT-4o mini vs Mistral
Mistral is the stronger model overall, scoring 29.9 to 25.5 on the Noometry Index.
Last verified . 22 shared benchmarks.
Mistral AISummary
- They share 22 benchmarks with published results for both. GPT-4o mini scores higher in 5 categories and Mistral in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Mistral leads 22.2 to 8.7.
- The biggest single-benchmark swing is MMLU-Pro: 60.3% for GPT-4o mini and 27.7% for Mistral.
Side by side
| GPT-4o mini | Mistral | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 25.5 | 29.9 |
| Released | 2024-07-18 | — |
| Weights | Proprietary | Proprietary |
| Context window | 128K | — |
| Max output | 16K | — |
| Input $ / M tokens | $0.15 | — |
| Output $ / M tokens | $0.60 | — |
| Results tracked | 60 | 22 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Mistral leads
GPT-4o mini: 22.0 (#335), Mistral: 33.8 (#250)
| Benchmark | GPT-4o mini | Mistral |
|---|---|---|
| LMArena Coding | 1290 | 1162 |
| Aider Polyglot | 3.6% | — |
| WeirdML | 11.8% | — |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 43.1% | — |
| BigCodeBench Complete | 57.4% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use Not comparable
GPT-4o mini: 27.5 (#101), Mistral: —
| Benchmark | GPT-4o mini | Mistral |
|---|---|---|
| BALROG | 17.4% | — |
Reasoning Mistral leads
GPT-4o mini: 8.7 (#347), Mistral: 22.2 (#200)
| Benchmark | GPT-4o mini | Mistral |
|---|---|---|
| LMArena Hard Prompts | 1267 | 1149 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 10.7% | — |
| Kagi LLM Benchmark | 28.8% | — |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | 32.8% | — |
| Mystery Game Puzzles | 12% | — |
| DTBench | 54.4% | — |
| LiveBench Data Analysis | 50% | — |
| LMCA | 10.4% | — |
| Epoch Capabilities Index | 126.56 | — |
| LiveBench | 41.3% | — |
| PIQA | 88.7% | — |
Math Mistral leads
GPT-4o mini: 10.4 (#314), Mistral: 22.3 (#278)
| Benchmark | GPT-4o mini | Mistral |
|---|---|---|
| Omni-MATH | 28% | 7.2% |
| LMArena Math | 1267 | 1180 |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| OTIS Mock AIME 2024-2025 | 6.9% | — |
| LiveBench Math | 36.3% | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |
Knowledge GPT-4o mini leads
GPT-4o mini: 17.7 (#284), Mistral: 16.6 (#288)
| Benchmark | GPT-4o mini | Mistral |
|---|---|---|
| MMLU-Pro | 60.3% | 27.7% |
| GPQA (HELM) | 36.8% | 30.3% |
| LMArena Expert | 1235 | 1125 |
| GPQA Diamond | 37.7% | — |
| SimpleQA Verified | 8.3% | — |
| Confabulations | 37.2% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |
Multimodal Not comparable
GPT-4o mini: 25.9 (#122), Mistral: —
| Benchmark | GPT-4o mini | Mistral |
|---|---|---|
| LMArena Vision | 1066 | — |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
Multilingual GPT-4o mini leads
GPT-4o mini: 42.0 (#199), Mistral: 32.8 (#254)
| Benchmark | GPT-4o mini | Mistral |
|---|---|---|
| LMArena Non-English | 1266 | 1129 |
| LMArena Chinese | 1265 | 1109 |
| LMArena French | 1297 | 1180 |
| LMArena German | 1272 | 1155 |
| LMArena Japanese | 1216 | 1013 |
| LMArena Korean | 1195 | 1032 |
| LMArena Russian | 1275 | 1168 |
| LMArena Spanish | 1276 | 1143 |
Instruction Following GPT-4o mini leads
GPT-4o mini: 61.9 (#239), Mistral: 52.6 (#288)
| Benchmark | GPT-4o mini | Mistral |
|---|---|---|
| IFEval | 78.2% | 56.8% |
| LMArena Instruction Following | 1258 | 1152 |
| LiveBench Instruction Following | 56.8% | — |
Long Context GPT-4o mini leads
GPT-4o mini: 39.1 (#186), Mistral: 35.0 (#245)
| Benchmark | GPT-4o mini | Mistral |
|---|---|---|
| LMArena Longer Query | 1289 | 1153 |
Writing & Preference GPT-4o mini leads
GPT-4o mini: 39.5 (#248), Mistral: 37.0 (#260)
| Benchmark | GPT-4o mini | Mistral |
|---|---|---|
| LMArena Text | 1286 | 1165 |
| LMArena Creative Writing | 1268 | 1158 |
| WildBench | 79.1% | 66% |
| LMArena Multi-Turn | 1285 | 1147 |
| Short-Story Creative Writing | 67.2% | — |
| EQ-Bench Creative Writing | 873 | — |
| LiveBench Language | 28.6% | — |
Frequently asked questions
Is GPT-4o mini better than Mistral?
Mistral is the stronger model overall, scoring 29.9 to 25.5 on the Noometry Index.
Is GPT-4o mini or Mistral better for coding?
Mistral scores higher on coding benchmarks: 33.8 versus 22.0 in the Noometry coding category.
How many benchmarks do GPT-4o mini and Mistral share?
22 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and Mistral has 22.