Model comparison
Claude Sonnet 4 vs MiMo-V2-Pro
MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 40.8 on the Noometry Index.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. Claude Sonnet 4 scores higher in 3 categories and MiMo-V2-Pro in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where MiMo-V2-Pro leads 41.5 to 33.7.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 200K.
Side by side
| Claude Sonnet 4 | MiMo-V2-Pro | |
|---|---|---|
| Provider | Anthropic | Xiaomi |
| Noometry Index | 40.8 | 43.0 |
| Released | 2025-05-22 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 1.05M |
| Max output | 64K | 131K |
| Input $ / M tokens | $3 | $0.43 |
| Output $ / M tokens | $15 | $0.87 |
| Results tracked | 58 | 23 |
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Category by category
Coding Too close to call
Claude Sonnet 4: 43.5 (#88), MiMo-V2-Pro: 43.8 (#83)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Pro |
|---|---|---|
| LMArena Coding | 1414 | 1476 |
| ALE-Bench | 655.35 | 785.17 |
| SWE-bench Verified (bash only) | 64.9% | — |
| Aider Polyglot | 61.3% | — |
| LMArena WebDev | — | 1433 |
| SciCode | 40% | — |
| GSO | 4.9% | — |
| WeirdML | 46.1% | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4: 38.5 (#31), MiMo-V2-Pro: —
| Benchmark | Claude Sonnet 4 | MiMo-V2-Pro |
|---|---|---|
| TheAgentCompany | 33.1% | — |
| Cybench | 35% | — |
| DeepResearch Bench | 46.6% | — |
| OSWorld | 43.9% | — |
| METR Time Horizons | 62% | — |
Reasoning Too close to call
Claude Sonnet 4: 22.9 (#187), MiMo-V2-Pro: 22.1 (#206)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Pro |
|---|---|---|
| LMArena Hard Prompts | 1372 | 1457 |
| ARC-AGI-2 | 5.9% | — |
| SimpleBench | 45.5% | — |
| Kagi LLM Benchmark | 73% | — |
| NYT Connections (extended) | — | 25.8% |
| ARC-AGI-1 | 40% | — |
| CritPt | 0.3% | — |
| EnigmaEval | 3.1% | — |
| Thematic Generalization | — | 45.9% |
| DTBench | 77.1% | — |
| LMCA | 29% | — |
| Epoch Capabilities Index | 141.69 | — |
| ForecastBench | 60.2 | — |
Math Claude Sonnet 4 leads
Claude Sonnet 4: 43.3 (#80), MiMo-V2-Pro: 39.5 (#102)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1375 | 1447 |
| OTIS Mock AIME 2024-2025 | 71.1% | — |
| Omni-MATH | 60.2% | — |
| MATH Level 5 | 84.4% | — |
| FrontierMath (Feb 2025 set) | 4.1% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Too close to call
Claude Sonnet 4: 41.8 (#108), MiMo-V2-Pro: 41.4 (#111)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1372 | 1478 |
| GPQA Diamond | 79.2% | — |
| Humanity's Last Exam | 7.8% | — |
| MMLU-Pro | 84.3% | — |
| Confabulations | 13.2% | — |
| Vectara Hallucination Rate | 10.3% | — |
| GPQA (HELM) | 70.6% | — |
Multimodal Not comparable
Claude Sonnet 4: 26.2 (#121), MiMo-V2-Pro: —
| Benchmark | Claude Sonnet 4 | MiMo-V2-Pro |
|---|---|---|
| LMArena Vision | 1191 | — |
| GeoBench | 37% | — |
| VPCT | 34% | — |
| MindCube | 44.8% | — |
Multilingual MiMo-V2-Pro leads
Claude Sonnet 4: 46.7 (#156), MiMo-V2-Pro: 52.7 (#81)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1333 | 1416 |
| LMArena Chinese | 1350 | 1456 |
| LMArena French | 1363 | 1469 |
| LMArena German | 1331 | 1417 |
| LMArena Japanese | 1302 | 1366 |
| LMArena Korean | 1291 | 1400 |
| LMArena Russian | 1355 | 1427 |
| LMArena Spanish | 1357 | 1457 |
Instruction Following MiMo-V2-Pro leads
Claude Sonnet 4: 71.7 (#145), MiMo-V2-Pro: 76.0 (#49)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1376 | 1445 |
| IFEval | 84% | — |
Long Context MiMo-V2-Pro leads
Claude Sonnet 4: 33.7 (#259), MiMo-V2-Pro: 41.5 (#138)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1398 | 1455 |
| Fiction.LiveBench | 46.9% | — |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |
Writing & Preference MiMo-V2-Pro leads
Claude Sonnet 4: 57.1 (#132), MiMo-V2-Pro: 62.8 (#70)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1351 | 1436 |
| LMArena Creative Writing | 1345 | 1415 |
| LMArena Multi-Turn | 1376 | 1456 |
| Short-Story Creative Writing | 81.4% | — |
| EQ-Bench Creative Writing | 1483 | — |
| WildBench | 83.8% | — |
Frequently asked questions
Is Claude Sonnet 4 better than MiMo-V2-Pro?
MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 40.8 on the Noometry Index.
Which is cheaper, Claude Sonnet 4 or MiMo-V2-Pro?
MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; Claude Sonnet 4 lists at $3 and $15.
Is Claude Sonnet 4 or MiMo-V2-Pro better for coding?
They score almost the same on coding (43.5 vs 43.8); test both on your own repository before choosing.
Which has the bigger context window?
MiMo-V2-Pro does, with 1.05M tokens against 200K.
How many benchmarks do Claude Sonnet 4 and MiMo-V2-Pro share?
18 benchmarks have published results for both models. Claude Sonnet 4 has 58 scored results on Noometry and MiMo-V2-Pro has 23.