Model comparison
MiniMax-M2.1 vs o3
o3 is the stronger model overall, scoring 47.5 to 38.9 on the Noometry Index. MiniMax-M2.1 costs 6.7× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
MiniMaxSummary
- They share 18 benchmarks with published results for both. MiniMax-M2.1 scores higher in 1 category and o3 in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o3 leads 54.6 to 38.3.
- MiniMax-M2.1 is cheaper at $0.30 / $1.20 per million input/output tokens, against $2 / $8 for o3.
- MiniMax-M2.1 accepts more context: 205K tokens versus 200K.
- MiniMax-M2.1 has downloadable open weights; the other is API-only.
Side by side
| MiniMax-M2.1 | o3 | |
|---|---|---|
| Provider | MiniMax | OpenAI |
| Noometry Index | 38.9 | 47.5 |
| Released | 2025-12-23 | 2025-04-16 |
| Weights | Open | Proprietary |
| Context window | 205K | 200K |
| Max output | 131K | 100K |
| Input $ / M tokens | $0.30 | $2 |
| Output $ / M tokens | $1.20 | $8 |
| Results tracked | 22 | 63 |
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Category by category
Coding o3 leads
MiniMax-M2.1: 40.4 (#143), o3: 46.8 (#64)
| Benchmark | MiniMax-M2.1 | o3 |
|---|---|---|
| LMArena Coding | 1421 | 1408 |
| ALE-Bench | 623.83 | 933.55 |
| SWE-bench Verified | — | 62.3% |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| LMArena WebDev | 1384 | — |
| GSO | — | 8.8% |
| WeirdML | — | 52.4% |
| CadEval | — | 74% |
Agentic & Tool Use o3 leads
MiniMax-M2.1: 27.9 (#98), o3: 34.5 (#44)
| Benchmark | MiniMax-M2.1 | o3 |
|---|---|---|
| Terminal-Bench | 36.6% | — |
| Berkeley Function Calling Leaderboard | — | 63% |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |
Reasoning o3 leads
MiniMax-M2.1: 16.6 (#302), o3: 32.0 (#78)
| Benchmark | MiniMax-M2.1 | o3 |
|---|---|---|
| LMArena Hard Prompts | 1411 | 1402 |
| ARC-AGI-2 | — | 6.5% |
| SimpleBench | — | 53.1% |
| Kagi LLM Benchmark | — | 67.6% |
| NYT Connections (extended) | 11.2% | — |
| ARC-AGI-1 | — | 60.8% |
| CritPt | — | 1.4% |
| Chess Puzzles | — | 38% |
| EnigmaEval | — | 13.1% |
| Mystery Game Puzzles | — | 29% |
| DTBench | — | 84.8% |
| LMCA | — | 39.7% |
| Epoch Capabilities Index | — | 146.86 |
| ForecastBench | — | 62.5 |
Math o3 leads
MiniMax-M2.1: 38.3 (#138), o3: 50.2 (#58)
| Benchmark | MiniMax-M2.1 | o3 |
|---|---|---|
| LMArena Math | 1397 | 1426 |
| FrontierMath (Tiers 1-3) | — | 33.3% |
| OTIS Mock AIME 2024-2025 | — | 84.4% |
| Omni-MATH | — | 71.4% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge o3 leads
MiniMax-M2.1: 38.3 (#147), o3: 54.6 (#52)
| Benchmark | MiniMax-M2.1 | o3 |
|---|---|---|
| LMArena Expert | 1431 | 1402 |
| GPQA Diamond | — | 81.8% |
| Humanity's Last Exam | — | 20.3% |
| SimpleQA Verified | — | 49.4% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| Vectara Hallucination Rate | 11.8% | — |
| GPQA (HELM) | — | 75.3% |
Multimodal Not comparable
MiniMax-M2.1: —, o3: 41.4 (#36)
| Benchmark | MiniMax-M2.1 | o3 |
|---|---|---|
| LMArena Vision | — | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
Multilingual o3 leads
MiniMax-M2.1: 50.0 (#128), o3: 51.7 (#105)
| Benchmark | MiniMax-M2.1 | o3 |
|---|---|---|
| LMArena Non-English | 1378 | 1401 |
| LMArena Chinese | 1430 | 1437 |
| LMArena French | 1404 | 1430 |
| LMArena German | 1381 | 1420 |
| LMArena Japanese | 1287 | 1403 |
| LMArena Korean | 1298 | 1370 |
| LMArena Russian | 1387 | 1406 |
| LMArena Spanish | 1397 | 1395 |
Instruction Following MiniMax-M2.1 leads
MiniMax-M2.1: 73.8 (#112), o3: 72.8 (#127)
| Benchmark | MiniMax-M2.1 | o3 |
|---|---|---|
| LMArena Instruction Following | 1400 | 1368 |
| IFEval | — | 86.9% |
Long Context o3 leads
MiniMax-M2.1: 43.2 (#101), o3: 53.3 (#6)
| Benchmark | MiniMax-M2.1 | o3 |
|---|---|---|
| LMArena Longer Query | 1416 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |
Writing & Preference o3 leads
MiniMax-M2.1: 58.3 (#120), o3: 63.5 (#64)
| Benchmark | MiniMax-M2.1 | o3 |
|---|---|---|
| LMArena Text | 1392 | 1410 |
| LMArena Creative Writing | 1361 | 1359 |
| LMArena Multi-Turn | 1396 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| EQ-Bench Creative Writing | — | 1676 |
| WildBench | — | 86.1% |
Frequently asked questions
Is MiniMax-M2.1 better than o3?
o3 is the stronger model overall, scoring 47.5 to 38.9 on the Noometry Index. MiniMax-M2.1 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-M2.1 or o3?
MiniMax-M2.1 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-M2.1 or o3 better for coding?
o3 scores higher on coding benchmarks: 46.8 versus 40.4 in the Noometry coding category.
Which has the bigger context window?
MiniMax-M2.1 does, with 205K tokens against 200K.
How many benchmarks do MiniMax-M2.1 and o3 share?
18 benchmarks have published results for both models. MiniMax-M2.1 has 22 scored results on Noometry and o3 has 63.