Model comparison
GPT-4o mini vs Mistral Large 4
Mistral Large 4 is the stronger model overall, scoring 43.1 to 25.5 on the Noometry Index. GPT-4o mini costs 3.9× less per token, which makes it the better buy when Mistral Large 4's lead doesn't matter for your workload.
Last verified . 13 shared benchmarks.
Mistral AISummary
- They share 13 benchmarks with published results for both. GPT-4o mini scores higher in 0 categories and Mistral Large 4 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Mistral Large 4 leads 40.4 to 10.4.
- The biggest single-benchmark swing is SimpleQA Verified: 8.3% for GPT-4o mini and 20% for Mistral Large 4.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.68 / $2.09 for Mistral Large 4.
- Mistral Large 4 accepts more context: 1.05M tokens versus 128K.
Side by side
| GPT-4o mini | Mistral Large 4 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 25.5 | 43.1 |
| Released | 2024-07-18 | 2026-10-06 |
| Weights | Proprietary | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 16K | 262K |
| Input $ / M tokens | $0.15 | $0.68 |
| Output $ / M tokens | $0.60 | $2.09 |
| Results tracked | 60 | 15 |
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Category by category
Coding Mistral Large 4 leads
GPT-4o mini: 22.0 (#335), Mistral Large 4: 48.6 (#57)
| Benchmark | GPT-4o mini | Mistral Large 4 |
|---|---|---|
| LMArena Coding | 1290 | 1475 |
| Aider Polyglot | 3.6% | — |
| LMArena WebDev | — | 1541 |
| 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 4: —
| Benchmark | GPT-4o mini | Mistral Large 4 |
|---|---|---|
| BALROG | 17.4% | — |
Reasoning Mistral Large 4 leads
GPT-4o mini: 8.7 (#347), Mistral Large 4: 22.5 (#192)
| Benchmark | GPT-4o mini | Mistral Large 4 |
|---|---|---|
| LMArena Hard Prompts | 1267 | 1444 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 10.7% | — |
| Kagi LLM Benchmark | 28.8% | — |
| NYT Connections (extended) | — | 27.4% |
| 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 Large 4 leads
GPT-4o mini: 10.4 (#314), Mistral Large 4: 40.4 (#91)
| Benchmark | GPT-4o mini | Mistral Large 4 |
|---|---|---|
| LMArena Math | 1267 | 1488 |
| 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 4 leads
GPT-4o mini: 17.7 (#284), Mistral Large 4: 36.6 (#166)
| Benchmark | GPT-4o mini | Mistral Large 4 |
|---|---|---|
| SimpleQA Verified | 8.3% | 20% |
| LMArena Expert | 1235 | 1447 |
| GPQA Diamond | 37.7% | — |
| MMLU-Pro | 60.3% | — |
| Confabulations | 37.2% | — |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |
Multimodal Not comparable
GPT-4o mini: 25.9 (#122), Mistral Large 4: —
| Benchmark | GPT-4o mini | Mistral Large 4 |
|---|---|---|
| LMArena Vision | 1066 | — |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
Multilingual Mistral Large 4 leads
GPT-4o mini: 42.0 (#199), Mistral Large 4: 52.6 (#82)
| Benchmark | GPT-4o mini | Mistral Large 4 |
|---|---|---|
| LMArena Non-English | 1266 | 1415 |
| LMArena Chinese | 1265 | 1491 |
| LMArena Russian | 1275 | 1414 |
| LMArena French | 1297 | — |
| LMArena German | 1272 | — |
| LMArena Japanese | 1216 | — |
| LMArena Korean | 1195 | — |
| LMArena Spanish | 1276 | — |
Instruction Following Mistral Large 4 leads
GPT-4o mini: 61.9 (#239), Mistral Large 4: 75.0 (#76)
| Benchmark | GPT-4o mini | Mistral Large 4 |
|---|---|---|
| LMArena Instruction Following | 1258 | 1424 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
Long Context Mistral Large 4 leads
GPT-4o mini: 39.1 (#186), Mistral Large 4: 43.6 (#89)
| Benchmark | GPT-4o mini | Mistral Large 4 |
|---|---|---|
| LMArena Longer Query | 1289 | 1429 |
Writing & Preference Mistral Large 4 leads
GPT-4o mini: 39.5 (#248), Mistral Large 4: 60.4 (#97)
| Benchmark | GPT-4o mini | Mistral Large 4 |
|---|---|---|
| LMArena Text | 1286 | 1427 |
| LMArena Creative Writing | 1268 | 1361 |
| LMArena Multi-Turn | 1285 | 1424 |
| Short-Story Creative Writing | 67.2% | — |
| EQ-Bench Creative Writing | 873 | — |
| WildBench | 79.1% | — |
| LiveBench Language | 28.6% | — |
Frequently asked questions
Is GPT-4o mini better than Mistral Large 4?
Mistral Large 4 is the stronger model overall, scoring 43.1 to 25.5 on the Noometry Index. GPT-4o mini costs 3.9× less per token, which makes it the better buy when Mistral Large 4's lead doesn't matter for your workload.
Which is cheaper, GPT-4o mini or Mistral Large 4?
GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Mistral Large 4 lists at $0.68 and $2.09.
Is GPT-4o mini or Mistral Large 4 better for coding?
Mistral Large 4 scores higher on coding benchmarks: 48.6 versus 22.0 in the Noometry coding category.
Which has the bigger context window?
Mistral Large 4 does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4o mini and Mistral Large 4 share?
13 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and Mistral Large 4 has 15.