Model comparison
Ministral 8B vs o3
o3 is the stronger model overall, scoring 47.5 to 28.2 on the Noometry Index. Ministral 8B costs 23× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Last verified . 16 shared benchmarks.
Mistral AISummary
- They share 16 benchmarks with published results for both. Ministral 8B scores higher in 0 categories and o3 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o3 leads 54.6 to 12.6.
- The biggest single-benchmark swing is MATH Level 5: 14.9% for Ministral 8B and 97.8% for o3.
- Ministral 8B is cheaper at $0.15 / $0.15 per million input/output tokens, against $2 / $8 for o3.
- Ministral 8B accepts more context: 262K tokens versus 200K.
- Ministral 8B has downloadable open weights; the other is API-only.
Side by side
| Ministral 8B | o3 | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 28.2 | 47.5 |
| Released | 2024-10-01 | 2025-04-16 |
| Weights | Open | Proprietary |
| Context window | 262K | 200K |
| Max output | 262K | 100K |
| Input $ / M tokens | $0.15 | $2 |
| Output $ / M tokens | $0.15 | $8 |
| Results tracked | 17 | 63 |
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Category by category
Coding o3 leads
Ministral 8B: 35.0 (#230), o3: 46.8 (#64)
| Benchmark | Ministral 8B | o3 |
|---|---|---|
| LMArena Coding | 1202 | 1408 |
| SWE-bench Verified | — | 62.3% |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| GSO | — | 8.8% |
| WeirdML | — | 52.4% |
| CadEval | — | 74% |
| ALE-Bench | — | 933.55 |
Agentic & Tool Use o3 leads
Ministral 8B: 16.4 (#148), o3: 34.5 (#44)
| Benchmark | Ministral 8B | o3 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 11.1% | 63% |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |
Reasoning o3 leads
Ministral 8B: 18.4 (#281), o3: 32.0 (#78)
| Benchmark | Ministral 8B | o3 |
|---|---|---|
| LMArena Hard Prompts | 1191 | 1402 |
| DTBench | 45.7% | 84.8% |
| ARC-AGI-2 | — | 6.5% |
| SimpleBench | — | 53.1% |
| Kagi LLM Benchmark | — | 67.6% |
| ARC-AGI-1 | — | 60.8% |
| CritPt | — | 1.4% |
| Chess Puzzles | — | 38% |
| EnigmaEval | — | 13.1% |
| Mystery Game Puzzles | — | 29% |
| LMCA | — | 39.7% |
| Epoch Capabilities Index | — | 146.86 |
| ForecastBench | — | 62.5 |
Math o3 leads
Ministral 8B: 25.7 (#267), o3: 50.2 (#58)
| Benchmark | Ministral 8B | o3 |
|---|---|---|
| LMArena Math | 1188 | 1426 |
| MATH Level 5 | 14.9% | 97.8% |
| FrontierMath (Tiers 1-3) | — | 33.3% |
| OTIS Mock AIME 2024-2025 | — | 84.4% |
| Omni-MATH | — | 71.4% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge o3 leads
Ministral 8B: 12.6 (#297), o3: 54.6 (#52)
| Benchmark | Ministral 8B | o3 |
|---|---|---|
| GPQA Diamond | 27.1% | 81.8% |
| LMArena Expert | 1170 | 1402 |
| Humanity's Last Exam | — | 20.3% |
| SimpleQA Verified | — | 49.4% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| Vectara Hallucination Rate | 7.4% | — |
| GPQA (HELM) | — | 75.3% |
Multimodal Not comparable
Ministral 8B: —, o3: 41.4 (#36)
| Benchmark | Ministral 8B | o3 |
|---|---|---|
| LMArena Vision | — | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
Multilingual o3 leads
Ministral 8B: 35.1 (#247), o3: 51.7 (#105)
| Benchmark | Ministral 8B | o3 |
|---|---|---|
| LMArena Non-English | 1165 | 1401 |
| LMArena Chinese | 1193 | 1437 |
| LMArena Russian | 1195 | 1406 |
| LMArena French | — | 1430 |
| LMArena German | — | 1420 |
| LMArena Japanese | — | 1403 |
| LMArena Korean | — | 1370 |
| LMArena Spanish | — | 1395 |
Instruction Following o3 leads
Ministral 8B: 60.5 (#250), o3: 72.8 (#127)
| Benchmark | Ministral 8B | o3 |
|---|---|---|
| LMArena Instruction Following | 1161 | 1368 |
| IFEval | — | 86.9% |
Long Context o3 leads
Ministral 8B: 36.7 (#227), o3: 53.3 (#6)
| Benchmark | Ministral 8B | o3 |
|---|---|---|
| LMArena Longer Query | 1212 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |
Writing & Preference o3 leads
Ministral 8B: 39.6 (#246), o3: 63.5 (#64)
| Benchmark | Ministral 8B | o3 |
|---|---|---|
| LMArena Text | 1191 | 1410 |
| LMArena Creative Writing | 1175 | 1359 |
| LMArena Multi-Turn | 1166 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| EQ-Bench Creative Writing | — | 1676 |
| WildBench | — | 86.1% |
Frequently asked questions
Is Ministral 8B better than o3?
o3 is the stronger model overall, scoring 47.5 to 28.2 on the Noometry Index. Ministral 8B costs 23× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Which is cheaper, Ministral 8B or o3?
Ministral 8B is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; o3 lists at $2 and $8.
Is Ministral 8B or o3 better for coding?
o3 scores higher on coding benchmarks: 46.8 versus 35.0 in the Noometry coding category.
Which has the bigger context window?
Ministral 8B does, with 262K tokens against 200K.
How many benchmarks do Ministral 8B and o3 share?
16 benchmarks have published results for both models. Ministral 8B has 17 scored results on Noometry and o3 has 63.