Model comparison
MiniMax-M3 vs o3
o3 is the stronger model overall, scoring 47.5 to 43.8 on the Noometry Index. MiniMax-M3 costs 6.7× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Last verified . 29 shared benchmarks.
MiniMaxSummary
- They share 29 benchmarks with published results for both. MiniMax-M3 scores higher in 3 categories and o3 in 7 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where o3 leads 34.5 to 22.6.
- The biggest single-benchmark swing is Chess Puzzles: 14% for MiniMax-M3 and 38% for o3.
- MiniMax-M3 is cheaper at $0.30 / $1.20 per million input/output tokens, against $2 / $8 for o3.
- MiniMax-M3 accepts more context: 1M tokens versus 200K.
- MiniMax-M3 has downloadable open weights; the other is API-only.
Side by side
| MiniMax-M3 | o3 | |
|---|---|---|
| Provider | MiniMax | OpenAI |
| Noometry Index | 43.8 | 47.5 |
| Released | 2026-06-01 | 2025-04-16 |
| Weights | Open | Proprietary |
| Context window | 1M | 200K |
| Max output | 512K | 100K |
| Input $ / M tokens | $0.30 | $2 |
| Output $ / M tokens | $1.20 | $8 |
| Results tracked | 41 | 63 |
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Category by category
Coding o3 leads
MiniMax-M3: 41.8 (#118), o3: 46.8 (#64)
| Benchmark | MiniMax-M3 | o3 |
|---|---|---|
| LMArena Coding | 1469 | 1408 |
| ALE-Bench | 640.02 | 933.55 |
| SWE-bench Verified | — | 62.3% |
| FrontierCode | 14.7% | — |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| LMArena WebDev | 1482 | — |
| SciCode | 47.1% | — |
| GSO | — | 8.8% |
| WeirdML | — | 52.4% |
| CadEval | — | 74% |
Agentic & Tool Use o3 leads
MiniMax-M3: 22.6 (#130), o3: 34.5 (#44)
| Benchmark | MiniMax-M3 | o3 |
|---|---|---|
| APEX-Agents | 37.7% | — |
| Berkeley Function Calling Leaderboard | — | 63% |
| OSWorld 2.0 | 4.6% | — |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| GBAEval | 0.9% | — |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |
| Vending-Bench 2 | 2,158 | — |
Reasoning o3 leads
MiniMax-M3: 30.1 (#87), o3: 32.0 (#78)
| Benchmark | MiniMax-M3 | o3 |
|---|---|---|
| SimpleBench | 45.8% | 53.1% |
| CritPt | 3.7% | 1.4% |
| Chess Puzzles | 14% | 38% |
| LMArena Hard Prompts | 1447 | 1402 |
| Mystery Game Puzzles | 8% | 29% |
| DTBench | 78.9% | 84.8% |
| LMCA | 33.7% | 39.7% |
| Epoch Capabilities Index | 146.95 | 146.86 |
| ForecastBench | 61.4 | 62.5 |
| ARC-AGI-2 | — | 6.5% |
| Kagi LLM Benchmark | — | 67.6% |
| NYT Connections (extended) | 65.1% | — |
| ARC-AGI-1 | — | 60.8% |
| EnigmaEval | — | 13.1% |
| Surface Evolver Bench | 55% | — |
Math o3 leads
MiniMax-M3: 40.0 (#95), o3: 50.2 (#58)
| Benchmark | MiniMax-M3 | o3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 71.1% | 84.4% |
| LMArena Math | 1429 | 1426 |
| FrontierMath (Tiers 1-3) | — | 33.3% |
| ProofBench | 18% | — |
| Omni-MATH | — | 71.4% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge MiniMax-M3 leads
MiniMax-M3: 58.4 (#35), o3: 54.6 (#52)
| Benchmark | MiniMax-M3 | o3 |
|---|---|---|
| GPQA Diamond | 90.9% | 81.8% |
| LMArena Expert | 1461 | 1402 |
| Humanity's Last Exam | — | 20.3% |
| SimpleQA Verified | — | 49.4% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| GPQA (HELM) | — | 75.3% |
Multimodal o3 leads
MiniMax-M3: 40.2 (#51), o3: 41.4 (#36)
| Benchmark | MiniMax-M3 | o3 |
|---|---|---|
| LMArena Vision | 1253 | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
| LMArena Document | 1435 | — |
Multilingual MiniMax-M3 leads
MiniMax-M3: 53.0 (#75), o3: 51.7 (#105)
| Benchmark | MiniMax-M3 | o3 |
|---|---|---|
| LMArena Non-English | 1420 | 1401 |
| LMArena Chinese | 1463 | 1437 |
| LMArena French | 1447 | 1430 |
| LMArena German | 1426 | 1420 |
| LMArena Japanese | 1381 | 1403 |
| LMArena Korean | 1372 | 1370 |
| LMArena Russian | 1428 | 1406 |
| LMArena Spanish | 1432 | 1395 |
Instruction Following MiniMax-M3 leads
MiniMax-M3: 75.5 (#62), o3: 72.8 (#127)
| Benchmark | MiniMax-M3 | o3 |
|---|---|---|
| LMArena Instruction Following | 1433 | 1368 |
| IFEval | — | 86.9% |
Long Context o3 leads
MiniMax-M3: 44.2 (#72), o3: 53.3 (#6)
| Benchmark | MiniMax-M3 | o3 |
|---|---|---|
| LMArena Longer Query | 1445 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |
Writing & Preference o3 leads
MiniMax-M3: 62.1 (#83), o3: 63.5 (#64)
| Benchmark | MiniMax-M3 | o3 |
|---|---|---|
| LMArena Text | 1433 | 1410 |
| LMArena Creative Writing | 1404 | 1359 |
| LMArena Multi-Turn | 1442 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| EQ-Bench Creative Writing | — | 1676 |
| WildBench | — | 86.1% |
| EQ-Bench 4 | 1150 | — |
Frequently asked questions
Is MiniMax-M3 better than o3?
o3 is the stronger model overall, scoring 47.5 to 43.8 on the Noometry Index. MiniMax-M3 costs 6.7× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Which is cheaper, MiniMax-M3 or o3?
MiniMax-M3 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; o3 lists at $2 and $8.
Is MiniMax-M3 or o3 better for coding?
o3 scores higher on coding benchmarks: 46.8 versus 41.8 in the Noometry coding category.
Which has the bigger context window?
MiniMax-M3 does, with 1M tokens against 200K.
How many benchmarks do MiniMax-M3 and o3 share?
29 benchmarks have published results for both models. MiniMax-M3 has 41 scored results on Noometry and o3 has 63.