Model comparison
Claude Sonnet 4 vs MiMo-V2-Omni
MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 40.6 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-Omni in 6 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in multimodal, where MiMo-V2-Omni leads 37.9 to 25.6.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.
- MiMo-V2-Omni accepts more context: 262K tokens versus 200K.
Side by side
| Claude Sonnet 4 | MiMo-V2-Omni | |
|---|---|---|
| Provider | Anthropic | Xiaomi |
| Noometry Index | 40.6 | 42.9 |
| Released | 2025-05-22 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 262K |
| Max output | 64K | 131K |
| Input $ / M tokens | $3 | $0.14 |
| Output $ / M tokens | $15 | $0.28 |
| Results tracked | 58 | 18 |
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Category by category
Coding Claude Sonnet 4 leads
Claude Sonnet 4: 44.0 (#70), MiMo-V2-Omni: 42.7 (#87)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1414 | 1467 |
| SWE-bench Verified (bash only) | 64.9% | — |
| Aider Polyglot | 61.3% | — |
| SciCode | 40% | — |
| GSO | 4.9% | — |
| WeirdML | 46.1% | — |
| ALE-Bench | 655.35 | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4: 38.3 (#29), MiMo-V2-Omni: —
| Benchmark | Claude Sonnet 4 | MiMo-V2-Omni |
|---|---|---|
| TheAgentCompany | 33.1% | — |
| Cybench | 35% | — |
| DeepResearch Bench | 46.6% | — |
| OSWorld | 43.9% | — |
| METR Time Horizons | 62% | — |
Reasoning MiMo-V2-Omni leads
Claude Sonnet 4: 23.0 (#169), MiMo-V2-Omni: 28.6 (#86)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1372 | 1445 |
| ARC-AGI-2 | 5.9% | — |
| SimpleBench | 45.5% | — |
| Kagi LLM Benchmark | 73% | — |
| ARC-AGI-1 | 40% | — |
| CritPt | 0.3% | — |
| EnigmaEval | 3.1% | — |
| DTBench | 77.1% | — |
| LMCA | 29% | — |
| Epoch Capabilities Index | 141.69 | — |
| ForecastBench | 60.2 | — |
Math Claude Sonnet 4 leads
Claude Sonnet 4: 41.5 (#71), MiMo-V2-Omni: 36.4 (#112)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | 1375 | 1432 |
| 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 Claude Sonnet 4 leads
Claude Sonnet 4: 41.6 (#99), MiMo-V2-Omni: 39.9 (#114)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1371 | 1449 |
| 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 MiMo-V2-Omni leads
Claude Sonnet 4: 25.6 (#116), MiMo-V2-Omni: 37.9 (#62)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | 1191 | 1228 |
| GeoBench | 37% | — |
| VPCT | 34% | — |
| MindCube | 44.8% | — |
Multilingual MiMo-V2-Omni leads
Claude Sonnet 4: 46.9 (#151), MiMo-V2-Omni: 52.0 (#97)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1333 | 1404 |
| LMArena Chinese | 1351 | 1469 |
| LMArena French | 1364 | 1448 |
| LMArena German | 1331 | 1398 |
| LMArena Japanese | 1301 | 1318 |
| LMArena Korean | 1293 | 1355 |
| LMArena Russian | 1355 | 1412 |
| LMArena Spanish | 1356 | 1432 |
Instruction Following MiMo-V2-Omni leads
Claude Sonnet 4: 71.8 (#141), MiMo-V2-Omni: 75.4 (#62)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1375 | 1428 |
| IFEval | 84% | — |
Long Context MiMo-V2-Omni leads
Claude Sonnet 4: 33.6 (#254), MiMo-V2-Omni: 44.1 (#72)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1398 | 1442 |
| Fiction.LiveBench | 46.9% | — |
Writing & Preference MiMo-V2-Omni leads
Claude Sonnet 4: 57.3 (#127), MiMo-V2-Omni: 61.6 (#83)
| Benchmark | Claude Sonnet 4 | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1351 | 1424 |
| LMArena Creative Writing | 1345 | 1393 |
| LMArena Multi-Turn | 1376 | 1446 |
| 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-Omni?
MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 40.6 on the Noometry Index.
Which is cheaper, Claude Sonnet 4 or MiMo-V2-Omni?
MiMo-V2-Omni is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Claude Sonnet 4 lists at $3 and $15.
Is Claude Sonnet 4 or MiMo-V2-Omni better for coding?
Claude Sonnet 4 scores higher on coding benchmarks: 44.0 versus 42.7 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Omni does, with 262K tokens against 200K.
How many benchmarks do Claude Sonnet 4 and MiMo-V2-Omni share?
18 benchmarks have published results for both models. Claude Sonnet 4 has 58 scored results on Noometry and MiMo-V2-Omni has 18.