Model comparison
MiMo-V2-Pro vs o3
o3 is the stronger model overall, scoring 47.5 to 43.0 on the Noometry Index. MiMo-V2-Pro costs 6.4× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
Summary
- They share 19 benchmarks with published results for both. MiMo-V2-Pro scores higher in 2 categories and o3 in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o3 leads 54.6 to 41.4.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $2 / $8 for o3.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 200K.
Side by side
| MiMo-V2-Pro | o3 | |
|---|---|---|
| Provider | Xiaomi | OpenAI |
| Noometry Index | 43.0 | 47.5 |
| Released | 2026-03-18 | 2025-04-16 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 200K |
| Max output | 131K | 100K |
| Input $ / M tokens | $0.43 | $2 |
| Output $ / M tokens | $0.87 | $8 |
| Results tracked | 23 | 63 |
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Category by category
Coding o3 leads
MiMo-V2-Pro: 43.8 (#83), o3: 46.8 (#64)
| Benchmark | MiMo-V2-Pro | o3 |
|---|---|---|
| LMArena Coding | 1476 | 1408 |
| ALE-Bench | 785.17 | 933.55 |
| SWE-bench Verified | — | 62.3% |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| LMArena WebDev | 1433 | — |
| GSO | — | 8.8% |
| WeirdML | — | 52.4% |
| CadEval | — | 74% |
Agentic & Tool Use Not comparable
MiMo-V2-Pro: —, o3: 34.5 (#44)
| Benchmark | MiMo-V2-Pro | o3 |
|---|---|---|
| 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
MiMo-V2-Pro: 22.1 (#206), o3: 32.0 (#78)
| Benchmark | MiMo-V2-Pro | o3 |
|---|---|---|
| LMArena Hard Prompts | 1457 | 1402 |
| ARC-AGI-2 | — | 6.5% |
| SimpleBench | — | 53.1% |
| Kagi LLM Benchmark | — | 67.6% |
| NYT Connections (extended) | 25.8% | — |
| ARC-AGI-1 | — | 60.8% |
| CritPt | — | 1.4% |
| Chess Puzzles | — | 38% |
| EnigmaEval | — | 13.1% |
| Thematic Generalization | 45.9% | — |
| Mystery Game Puzzles | — | 29% |
| DTBench | — | 84.8% |
| LMCA | — | 39.7% |
| Epoch Capabilities Index | — | 146.86 |
| ForecastBench | — | 62.5 |
Math o3 leads
MiMo-V2-Pro: 39.5 (#102), o3: 50.2 (#58)
| Benchmark | MiMo-V2-Pro | o3 |
|---|---|---|
| LMArena Math | 1447 | 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
MiMo-V2-Pro: 41.4 (#111), o3: 54.6 (#52)
| Benchmark | MiMo-V2-Pro | o3 |
|---|---|---|
| LMArena Expert | 1478 | 1402 |
| GPQA Diamond | — | 81.8% |
| Humanity's Last Exam | — | 20.3% |
| SimpleQA Verified | — | 49.4% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| GPQA (HELM) | — | 75.3% |
Multimodal Not comparable
MiMo-V2-Pro: —, o3: 41.4 (#36)
| Benchmark | MiMo-V2-Pro | o3 |
|---|---|---|
| LMArena Vision | — | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
Multilingual MiMo-V2-Pro leads
MiMo-V2-Pro: 52.7 (#81), o3: 51.7 (#105)
| Benchmark | MiMo-V2-Pro | o3 |
|---|---|---|
| LMArena Non-English | 1416 | 1401 |
| LMArena Chinese | 1456 | 1437 |
| LMArena French | 1469 | 1430 |
| LMArena German | 1417 | 1420 |
| LMArena Japanese | 1366 | 1403 |
| LMArena Korean | 1400 | 1370 |
| LMArena Russian | 1427 | 1406 |
| LMArena Spanish | 1457 | 1395 |
Instruction Following MiMo-V2-Pro leads
MiMo-V2-Pro: 76.0 (#49), o3: 72.8 (#127)
| Benchmark | MiMo-V2-Pro | o3 |
|---|---|---|
| LMArena Instruction Following | 1445 | 1368 |
| IFEval | — | 86.9% |
Long Context o3 leads
MiMo-V2-Pro: 41.5 (#138), o3: 53.3 (#6)
| Benchmark | MiMo-V2-Pro | o3 |
|---|---|---|
| CL-bench | 15.7% | 17.8% |
| LMArena Longer Query | 1455 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench Life | 6.9% | — |
Writing & Preference Too close to call
MiMo-V2-Pro: 62.8 (#70), o3: 63.5 (#64)
| Benchmark | MiMo-V2-Pro | o3 |
|---|---|---|
| LMArena Text | 1436 | 1410 |
| LMArena Creative Writing | 1415 | 1359 |
| LMArena Multi-Turn | 1456 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| EQ-Bench Creative Writing | — | 1676 |
| WildBench | — | 86.1% |
Frequently asked questions
Is MiMo-V2-Pro better than o3?
o3 is the stronger model overall, scoring 47.5 to 43.0 on the Noometry Index. MiMo-V2-Pro costs 6.4× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Which is cheaper, MiMo-V2-Pro or o3?
MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; o3 lists at $2 and $8.
Is MiMo-V2-Pro or o3 better for coding?
o3 scores higher on coding benchmarks: 46.8 versus 43.8 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Pro does, with 1.05M tokens against 200K.
How many benchmarks do MiMo-V2-Pro and o3 share?
19 benchmarks have published results for both models. MiMo-V2-Pro has 23 scored results on Noometry and o3 has 63.