Model comparison
GPT-4.1 vs Ministral 3B
GPT-4.1 is the stronger model overall, scoring 35.7 to 25.6 on the Noometry Index. Ministral 3B costs 88× less per token, which makes it the better buy when GPT-4.1's lead doesn't matter for your workload.
Last verified . 6 shared benchmarks.
Mistral AISummary
- They share 6 benchmarks with published results for both. GPT-4.1 scores higher in 1 category and Ministral 3B in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-4.1 leads 37.0 to 10.4.
- The biggest single-benchmark swing is MATH Level 5: 83% for GPT-4.1 and 14.4% for Ministral 3B.
- Ministral 3B is cheaper at $0.04 / $0.04 per million input/output tokens, against $2 / $8 for GPT-4.1.
- GPT-4.1 accepts more context: 1.05M tokens versus 128K.
- Ministral 3B has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 | Ministral 3B | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 35.7 | 25.6 |
| Released | 2025-04-14 | 2024-10-01 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 33K | 128K |
| Input $ / M tokens | $2 | $0.04 |
| Output $ / M tokens | $8 | $0.04 |
| Results tracked | 52 | 6 |
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Category by category
Coding Not comparable
GPT-4.1: 34.2 (#228), Ministral 3B: —
| Benchmark | GPT-4.1 | Ministral 3B |
|---|---|---|
| SWE-bench Verified | 48.5% | — |
| SWE-bench Verified (bash only) | 39.6% | — |
| Aider Polyglot | 52.4% | — |
| WeirdML | 39% | — |
| LMArena Coding | 1391 | — |
| CadEval | 42% | — |
| ALE-Bench | 558.1 | — |
Agentic & Tool Use Not comparable
GPT-4.1: 34.4 (#40), Ministral 3B: —
| Benchmark | GPT-4.1 | Ministral 3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 54% | — |
Reasoning Ministral 3B leads
GPT-4.1: 11.7 (#334), Ministral 3B: 17.7 (#278)
| Benchmark | GPT-4.1 | Ministral 3B |
|---|---|---|
| DTBench | 68.3% | 51.7% |
| LMCA | 25.6% | 5.5% |
| Epoch Capabilities Index | 136.79 | 118.08 |
| ARC-AGI-2 | 0.4% | — |
| SimpleBench | 27% | — |
| Kagi LLM Benchmark | 52.3% | — |
| ARC-AGI-1 | 5.5% | — |
| Chess Puzzles | 6% | — |
| EnigmaEval | 2.2% | — |
| LMArena Hard Prompts | 1384 | — |
| ForecastBench | 61.5 | — |
Math Ministral 3B leads
GPT-4.1: 21.4 (#269), Ministral 3B: 24.5 (#257)
| Benchmark | GPT-4.1 | Ministral 3B |
|---|---|---|
| MATH Level 5 | 83% | 14.4% |
| FrontierMath (Tiers 1-3) | 6% | — |
| OTIS Mock AIME 2024-2025 | 38.3% | — |
| Omni-MATH | 47.1% | — |
| LMArena Math | 1369 | — |
| FrontierMath (Feb 2025 set) | 5.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge GPT-4.1 leads
GPT-4.1: 37.0 (#152), Ministral 3B: 10.4 (#297)
| Benchmark | GPT-4.1 | Ministral 3B |
|---|---|---|
| GPQA Diamond | 66.9% | 25.3% |
| Vectara Hallucination Rate | 5.6% | 7.3% |
| Humanity's Last Exam | 5.4% | — |
| SimpleQA Verified | 31.1% | — |
| MMLU-Pro | 81.1% | — |
| GPQA (HELM) | 65.9% | — |
| LMArena Expert | 1364 | — |
Multimodal Not comparable
GPT-4.1: 37.5 (#66), Ministral 3B: —
| Benchmark | GPT-4.1 | Ministral 3B |
|---|---|---|
| LMArena Vision | 1210 | — |
| GeoBench | 72% | — |
Multilingual Not comparable
GPT-4.1: 49.6 (#128), Ministral 3B: —
| Benchmark | GPT-4.1 | Ministral 3B |
|---|---|---|
| LMArena Non-English | 1370 | — |
| LMArena Chinese | 1382 | — |
| LMArena French | 1383 | — |
| LMArena German | 1380 | — |
| LMArena Japanese | 1320 | — |
| LMArena Korean | 1339 | — |
| LMArena Russian | 1377 | — |
| LMArena Spanish | 1375 | — |
Instruction Following Not comparable
GPT-4.1: 71.5 (#148), Ministral 3B: —
| Benchmark | GPT-4.1 | Ministral 3B |
|---|---|---|
| IFEval | 83.8% | — |
| LMArena Instruction Following | 1367 | — |
Long Context Not comparable
GPT-4.1: 40.0 (#158), Ministral 3B: —
| Benchmark | GPT-4.1 | Ministral 3B |
|---|---|---|
| Fiction.LiveBench | 63.9% | — |
| LMArena Longer Query | 1385 | — |
Writing & Preference Not comparable
GPT-4.1: 57.8 (#120), Ministral 3B: —
| Benchmark | GPT-4.1 | Ministral 3B |
|---|---|---|
| LMArena Text | 1383 | — |
| LMArena Creative Writing | 1363 | — |
| EQ-Bench Creative Writing | 1420 | — |
| WildBench | 85.4% | — |
| LMArena Multi-Turn | 1398 | — |
Frequently asked questions
Is GPT-4.1 better than Ministral 3B?
GPT-4.1 is the stronger model overall, scoring 35.7 to 25.6 on the Noometry Index. Ministral 3B costs 88× less per token, which makes it the better buy when GPT-4.1's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 or Ministral 3B?
Ministral 3B is cheaper. It lists at $0.04 per million input tokens and $0.04 per million output tokens; GPT-4.1 lists at $2 and $8.
Which has the bigger context window?
GPT-4.1 does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4.1 and Ministral 3B share?
6 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and Ministral 3B has 6.