Model comparison
GPT-4o mini vs Mistral Large 3
Mistral Large 3 is the stronger model overall, scoring 39.1 to 25.5 on the Noometry Index.
Last verified . 20 shared benchmarks.
Mistral AISummary
- They share 20 benchmarks with published results for both. GPT-4o mini scores higher in 0 categories and Mistral Large 3 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Mistral Large 3 leads 38.7 to 10.4.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 28.8% for GPT-4o mini and 50.9% for Mistral Large 3.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.25 / $0.75 for Mistral Large 3.
- Mistral Large 3 accepts more context: 262K tokens versus 128K.
- Mistral Large 3 has downloadable open weights; the other is API-only.
Side by side
| GPT-4o mini | Mistral Large 3 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 25.5 | 39.1 |
| Released | 2024-07-18 | 2025-12-02 |
| Weights | Proprietary | Open |
| Context window | 128K | 262K |
| Max output | 16K | 8K |
| Input $ / M tokens | $0.15 | $0.25 |
| Output $ / M tokens | $0.60 | $0.75 |
| Results tracked | 60 | 24 |
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Category by category
Coding Mistral Large 3 leads
GPT-4o mini: 22.0 (#335), Mistral Large 3: 34.4 (#237)
| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Coding | 1290 | 1448 |
| Aider Polyglot | 3.6% | — |
| LMArena WebDev | — | 1230 |
| 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 Large 3: —
| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| BALROG | 17.4% | — |
Reasoning Mistral Large 3 leads
GPT-4o mini: 8.7 (#347), Mistral Large 3: 15.2 (#319)
| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | 50.9% |
| LMArena Hard Prompts | 1267 | 1429 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 10.7% | — |
| NYT Connections (extended) | — | 7.5% |
| Chess Puzzles | 0% | — |
| Thematic Generalization | — | 23% |
| 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 Large 3 leads
GPT-4o mini: 10.4 (#314), Mistral Large 3: 38.7 (#129)
| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1267 | 1414 |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| OTIS Mock AIME 2024-2025 | 6.9% | — |
| Omni-MATH | 28% | — |
| LiveBench Math | 36.3% | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |
Knowledge Mistral Large 3 leads
GPT-4o mini: 17.7 (#284), Mistral Large 3: 36.0 (#177)
| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Expert | 1235 | 1421 |
| GPQA Diamond | 37.7% | — |
| SimpleQA Verified | 8.3% | — |
| MMLU-Pro | 60.3% | — |
| Confabulations | 37.2% | — |
| Vectara Hallucination Rate | — | 14.5% |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |
Multimodal Mistral Large 3 leads
GPT-4o mini: 25.9 (#122), Mistral Large 3: 38.2 (#66)
| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1066 | 1221 |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
Multilingual Mistral Large 3 leads
GPT-4o mini: 42.0 (#199), Mistral Large 3: 52.5 (#84)
| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1266 | 1413 |
| LMArena Chinese | 1265 | 1447 |
| LMArena French | 1297 | 1455 |
| LMArena German | 1272 | 1437 |
| LMArena Japanese | 1216 | 1394 |
| LMArena Korean | 1195 | 1384 |
| LMArena Russian | 1275 | 1411 |
| LMArena Spanish | 1276 | 1440 |
Instruction Following Mistral Large 3 leads
GPT-4o mini: 61.9 (#239), Mistral Large 3: 74.0 (#108)
| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1258 | 1403 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
Long Context Mistral Large 3 leads
GPT-4o mini: 39.1 (#186), Mistral Large 3: 43.1 (#105)
| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1289 | 1413 |
Writing & Preference Mistral Large 3 leads
GPT-4o mini: 39.5 (#248), Mistral Large 3: 60.0 (#101)
| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1286 | 1428 |
| LMArena Creative Writing | 1268 | 1386 |
| EQ-Bench Creative Writing | 873 | 1412 |
| LMArena Multi-Turn | 1285 | 1429 |
| Short-Story Creative Writing | 67.2% | — |
| WildBench | 79.1% | — |
| LiveBench Language | 28.6% | — |
Frequently asked questions
Is GPT-4o mini better than Mistral Large 3?
Mistral Large 3 is the stronger model overall, scoring 39.1 to 25.5 on the Noometry Index.
Which is cheaper, GPT-4o mini or Mistral Large 3?
GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Mistral Large 3 lists at $0.25 and $0.75.
Is GPT-4o mini or Mistral Large 3 better for coding?
Mistral Large 3 scores higher on coding benchmarks: 34.4 versus 22.0 in the Noometry coding category.
Which has the bigger context window?
Mistral Large 3 does, with 262K tokens against 128K.
How many benchmarks do GPT-4o mini and Mistral Large 3 share?
20 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and Mistral Large 3 has 24.