Model comparison
GPT-4.1 mini vs Ministral 8B
GPT-4.1 mini is the stronger model overall, scoring 33.5 to 27.8 on the Noometry Index. Ministral 8B costs 7.0× less per token, which makes it the better buy when GPT-4.1 mini's lead doesn't matter for your workload.
Last verified . 16 shared benchmarks.
Mistral AISummary
- They share 16 benchmarks with published results for both. GPT-4.1 mini scores higher in 5 categories and Ministral 8B in 4 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-4.1 mini leads 34.7 to 12.5.
- The biggest single-benchmark swing is MATH Level 5: 87.3% for GPT-4.1 mini and 14.9% for Ministral 8B.
- Ministral 8B is cheaper at $0.10 / $0.10 per million input/output tokens, against $0.40 / $1.60 for GPT-4.1 mini.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 128K.
- Ministral 8B has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 mini | Ministral 8B | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 33.5 | 27.8 |
| Released | 2025-04-14 | 2024-10-01 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 33K | 128K |
| Input $ / M tokens | $0.40 | $0.10 |
| Output $ / M tokens | $1.60 | $0.10 |
| Results tracked | 47 | 17 |
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Category by category
Coding Ministral 8B leads
GPT-4.1 mini: 30.4 (#286), Ministral 8B: 34.4 (#226)
| Benchmark | GPT-4.1 mini | Ministral 8B |
|---|---|---|
| LMArena Coding | 1367 | 1202 |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| SciCode | 40.4% | — |
| WeirdML | 37.6% | — |
| BigCodeBench Instruct | 48.9% | — |
| CadEval | 16% | — |
Agentic & Tool Use GPT-4.1 mini leads
GPT-4.1 mini: 33.0 (#52), Ministral 8B: 16.2 (#140)
| Benchmark | GPT-4.1 mini | Ministral 8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 50.5% | 11.1% |
Reasoning Ministral 8B leads
GPT-4.1 mini: 10.9 (#335), Ministral 8B: 17.7 (#279)
| Benchmark | GPT-4.1 mini | Ministral 8B |
|---|---|---|
| LMArena Hard Prompts | 1349 | 1191 |
| DTBench | 68.8% | 45.7% |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 48.6% | — |
| ARC-AGI-1 | 3.5% | — |
| CritPt | 0% | — |
| Chess Puzzles | 7% | — |
| Mystery Game Puzzles | 7% | — |
| LMCA | 21.1% | — |
| Epoch Capabilities Index | 135.01 | — |
Math Too close to call
GPT-4.1 mini: 23.1 (#264), Ministral 8B: 23.7 (#262)
| Benchmark | GPT-4.1 mini | Ministral 8B |
|---|---|---|
| LMArena Math | 1343 | 1188 |
| MATH Level 5 | 87.3% | 14.9% |
| FrontierMath (Tiers 1-3) | 6.7% | — |
| OTIS Mock AIME 2024-2025 | 44.7% | — |
| Omni-MATH | 49.1% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
Knowledge GPT-4.1 mini leads
GPT-4.1 mini: 34.7 (#183), Ministral 8B: 12.5 (#292)
| Benchmark | GPT-4.1 mini | Ministral 8B |
|---|---|---|
| GPQA Diamond | 65.8% | 27.1% |
| LMArena Expert | 1338 | 1170 |
| SimpleQA Verified | 12.7% | — |
| MMLU-Pro | 78.3% | — |
| Vectara Hallucination Rate | — | 7.4% |
| GPQA (HELM) | 61.4% | — |
Multimodal Not comparable
GPT-4.1 mini: 35.2 (#77), Ministral 8B: —
| Benchmark | GPT-4.1 mini | Ministral 8B |
|---|---|---|
| LMArena Vision | 1181 | — |
Multilingual GPT-4.1 mini leads
GPT-4.1 mini: 45.9 (#161), Ministral 8B: 35.3 (#242)
| Benchmark | GPT-4.1 mini | Ministral 8B |
|---|---|---|
| LMArena Non-English | 1318 | 1165 |
| LMArena Chinese | 1329 | 1193 |
| LMArena Russian | 1324 | 1195 |
| LMArena French | 1357 | — |
| LMArena German | 1349 | — |
| LMArena Japanese | 1291 | — |
| LMArena Korean | 1298 | — |
| LMArena Spanish | 1319 | — |
Instruction Following GPT-4.1 mini leads
GPT-4.1 mini: 73.9 (#113), Ministral 8B: 60.7 (#245)
| Benchmark | GPT-4.1 mini | Ministral 8B |
|---|---|---|
| LMArena Instruction Following | 1332 | 1161 |
| IFEval | 90.4% | — |
Long Context Ministral 8B leads
GPT-4.1 mini: 31.8 (#270), Ministral 8B: 36.7 (#222)
| Benchmark | GPT-4.1 mini | Ministral 8B |
|---|---|---|
| LMArena Longer Query | 1344 | 1212 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference GPT-4.1 mini leads
GPT-4.1 mini: 48.8 (#193), Ministral 8B: 39.8 (#241)
| Benchmark | GPT-4.1 mini | Ministral 8B |
|---|---|---|
| LMArena Text | 1341 | 1191 |
| LMArena Creative Writing | 1300 | 1175 |
| LMArena Multi-Turn | 1354 | 1166 |
| EQ-Bench Creative Writing | 1147 | — |
| WildBench | 83.8% | — |
Frequently asked questions
Is GPT-4.1 mini better than Ministral 8B?
GPT-4.1 mini is the stronger model overall, scoring 33.5 to 27.8 on the Noometry Index. Ministral 8B costs 7.0× less per token, which makes it the better buy when GPT-4.1 mini's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 mini or Ministral 8B?
Ministral 8B is cheaper. It lists at $0.10 per million input tokens and $0.10 per million output tokens; GPT-4.1 mini lists at $0.40 and $1.60.
Is GPT-4.1 mini or Ministral 8B better for coding?
Ministral 8B scores higher on coding benchmarks: 34.4 versus 30.4 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4.1 mini and Ministral 8B share?
16 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Ministral 8B has 17.