Model comparison
GPT-4o mini vs Magistral Medium
Magistral Medium is the stronger model overall, scoring 35.2 to 25.5 on the Noometry Index. GPT-4o mini costs 10× less per token, which makes it the better buy when Magistral Medium's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
Mistral AISummary
- They share 19 benchmarks with published results for both. GPT-4o mini scores higher in 2 categories and Magistral Medium in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Magistral Medium leads 35.1 to 10.4.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 28.8% for GPT-4o mini and 16.2% for Magistral Medium.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $2 / $5 for Magistral Medium.
- Magistral Medium accepts more context: 262K tokens versus 128K.
- Magistral Medium has downloadable open weights; the other is API-only.
Side by side
| GPT-4o mini | Magistral Medium | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 25.5 | 35.2 |
| Released | 2024-07-18 | 2025-03-17 |
| Weights | Proprietary | Open |
| Context window | 128K | 262K |
| Max output | 16K | 16K |
| Input $ / M tokens | $0.15 | $2 |
| Output $ / M tokens | $0.60 | $5 |
| Results tracked | 60 | 22 |
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Category by category
Coding Magistral Medium leads
GPT-4o mini: 22.0 (#335), Magistral Medium: 39.1 (#161)
| Benchmark | GPT-4o mini | Magistral Medium |
|---|---|---|
| LMArena Coding | 1290 | 1319 |
| Aider Polyglot | 3.6% | — |
| SciCode | — | 39.2% |
| 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), Magistral Medium: —
| Benchmark | GPT-4o mini | Magistral Medium |
|---|---|---|
| BALROG | 17.4% | — |
Reasoning Too close to call
GPT-4o mini: 8.7 (#347), Magistral Medium: 8.6 (#348)
| Benchmark | GPT-4o mini | Magistral Medium |
|---|---|---|
| ARC-AGI-2 | 0% | 0% |
| Kagi LLM Benchmark | 28.8% | 16.2% |
| LMArena Hard Prompts | 1267 | 1267 |
| SimpleBench | 10.7% | — |
| ARC-AGI-1 | — | 6.1% |
| CritPt | — | 0.3% |
| 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 Magistral Medium leads
GPT-4o mini: 10.4 (#314), Magistral Medium: 35.1 (#189)
| Benchmark | GPT-4o mini | Magistral Medium |
|---|---|---|
| LMArena Math | 1267 | 1250 |
| 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 Magistral Medium leads
GPT-4o mini: 17.7 (#284), Magistral Medium: 33.5 (#202)
| Benchmark | GPT-4o mini | Magistral Medium |
|---|---|---|
| LMArena Expert | 1235 | 1223 |
| GPQA Diamond | 37.7% | — |
| SimpleQA Verified | 8.3% | — |
| 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), Magistral Medium: —
| Benchmark | GPT-4o mini | Magistral Medium |
|---|---|---|
| LMArena Vision | 1066 | — |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
Multilingual GPT-4o mini leads
GPT-4o mini: 42.0 (#199), Magistral Medium: 39.6 (#224)
| Benchmark | GPT-4o mini | Magistral Medium |
|---|---|---|
| LMArena Non-English | 1266 | 1232 |
| LMArena Chinese | 1265 | 1227 |
| LMArena French | 1297 | 1267 |
| LMArena German | 1272 | 1248 |
| LMArena Japanese | 1216 | 1175 |
| LMArena Korean | 1195 | 1125 |
| LMArena Russian | 1275 | 1224 |
| LMArena Spanish | 1276 | 1271 |
Instruction Following Magistral Medium leads
GPT-4o mini: 61.9 (#239), Magistral Medium: 66.0 (#211)
| Benchmark | GPT-4o mini | Magistral Medium |
|---|---|---|
| LMArena Instruction Following | 1258 | 1254 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
Long Context Too close to call
GPT-4o mini: 39.1 (#186), Magistral Medium: 39.3 (#183)
| Benchmark | GPT-4o mini | Magistral Medium |
|---|---|---|
| LMArena Longer Query | 1289 | 1295 |
Writing & Preference Magistral Medium leads
GPT-4o mini: 39.5 (#248), Magistral Medium: 46.3 (#219)
| Benchmark | GPT-4o mini | Magistral Medium |
|---|---|---|
| LMArena Text | 1286 | 1255 |
| LMArena Creative Writing | 1268 | 1245 |
| LMArena Multi-Turn | 1285 | 1275 |
| 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 Magistral Medium?
Magistral Medium is the stronger model overall, scoring 35.2 to 25.5 on the Noometry Index. GPT-4o mini costs 10× less per token, which makes it the better buy when Magistral Medium's lead doesn't matter for your workload.
Which is cheaper, GPT-4o mini or Magistral Medium?
GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Magistral Medium lists at $2 and $5.
Is GPT-4o mini or Magistral Medium better for coding?
Magistral Medium scores higher on coding benchmarks: 39.1 versus 22.0 in the Noometry coding category.
Which has the bigger context window?
Magistral Medium does, with 262K tokens against 128K.
How many benchmarks do GPT-4o mini and Magistral Medium share?
19 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and Magistral Medium has 22.