Model comparison
Claude Sonnet 4.6 vs MiMo-V2-Pro
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 43.0 on the Noometry Index. MiMo-V2-Pro costs 11× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Summary
- They share 21 benchmarks with published results for both. Claude Sonnet 4.6 scores higher in 8 categories and MiMo-V2-Pro in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Sonnet 4.6 leads 46.1 to 22.1.
- The biggest single-benchmark swing is NYT Connections (extended): 80.9% for Claude Sonnet 4.6 and 25.8% for MiMo-V2-Pro.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.6.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Sonnet 4.6 | MiMo-V2-Pro | |
|---|---|---|
| Provider | Anthropic | Xiaomi |
| Noometry Index | 50.3 | 43.0 |
| Released | 2026-02-17 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $3 | $0.43 |
| Output $ / M tokens | $15 | $0.87 |
| Results tracked | 57 | 23 |
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Category by category
Coding Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.3 (#67), MiMo-V2-Pro: 43.8 (#83)
| Benchmark | Claude Sonnet 4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena WebDev | 1522 | 1433 |
| LMArena Coding | 1504 | 1476 |
| ALE-Bench | 1,327 | 785.17 |
| SWE-bench Verified | 75.2% | — |
| DeepSWE | 29.9% | — |
| FrontierCode | 24.3% | — |
| SciCode | 46.8% | — |
| WeirdML | 66.1% | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4.6: 39.1 (#28), MiMo-V2-Pro: —
| Benchmark | Claude Sonnet 4.6 | MiMo-V2-Pro |
|---|---|---|
| Terminal-Bench | 53.4% | — |
| APEX-Agents | 43% | — |
| OSWorld 2.0 | 9.3% | — |
| DeepResearch Bench | 54.9% | — |
| OSWorld | 72.1% | — |
| ExploitBench | 23.6% | — |
| GBAEval | 48.8% | — |
| GDP.pdf | 18% | — |
| LMArena Search | 1221 | — |
| Vending-Bench 2 | 7,204 | — |
Reasoning Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.1 (#45), MiMo-V2-Pro: 22.1 (#206)
| Benchmark | Claude Sonnet 4.6 | MiMo-V2-Pro |
|---|---|---|
| NYT Connections (extended) | 80.9% | 25.8% |
| Thematic Generalization | 76.3% | 45.9% |
| LMArena Hard Prompts | 1484 | 1457 |
| ARC-AGI-2 | 60.4% | — |
| ARC-AGI-1 | 86.5% | — |
| CritPt | 3.1% | — |
| Chess Puzzles | 13% | — |
| Mystery Game Puzzles | 16% | — |
| DTBench | 89.9% | — |
| LMCA | 46.5% | — |
| Epoch Capabilities Index | 152.24 | — |
| ForecastBench | 62 | — |
Math Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 52.9 (#49), MiMo-V2-Pro: 39.5 (#102)
| Benchmark | Claude Sonnet 4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1462 | 1447 |
| OTIS Mock AIME 2024-2025 | 85.8% | — |
| ProofBench | 45% | — |
| FrontierMath (Feb 2025 set) | 32.4% | — |
| FrontierMath Tier 4 (v1) | 8.3% | — |
Knowledge Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 51.7 (#65), MiMo-V2-Pro: 41.4 (#111)
| Benchmark | Claude Sonnet 4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1500 | 1478 |
| GPQA Diamond | 87.4% | — |
| SimpleQA Verified | 35.5% | — |
| Vectara Hallucination Rate | 10.6% | — |
Multimodal Not comparable
Claude Sonnet 4.6: 38.0 (#68), MiMo-V2-Pro: —
| Benchmark | Claude Sonnet 4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Vision | 1283 | — |
| Blueprint-Bench 2 | 6.7% | — |
| LMArena Document | 1482 | — |
Multilingual Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 54.4 (#41), MiMo-V2-Pro: 52.7 (#81)
| Benchmark | Claude Sonnet 4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1440 | 1416 |
| LMArena Chinese | 1491 | 1456 |
| LMArena French | 1465 | 1469 |
| LMArena German | 1428 | 1417 |
| LMArena Japanese | 1420 | 1366 |
| LMArena Korean | 1411 | 1400 |
| LMArena Russian | 1440 | 1427 |
| LMArena Spanish | 1464 | 1457 |
Instruction Following Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 77.4 (#25), MiMo-V2-Pro: 76.0 (#49)
| Benchmark | Claude Sonnet 4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1475 | 1445 |
Long Context Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 45.3 (#44), MiMo-V2-Pro: 41.5 (#138)
| Benchmark | Claude Sonnet 4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1479 | 1455 |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |
Writing & Preference Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 70.2 (#22), MiMo-V2-Pro: 62.8 (#70)
| Benchmark | Claude Sonnet 4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1458 | 1436 |
| LMArena Creative Writing | 1435 | 1415 |
| LMArena Multi-Turn | 1464 | 1456 |
| EQ-Bench Creative Writing | 1810 | — |
| EQ-Bench 4 | 1207 | — |
Frequently asked questions
Is Claude Sonnet 4.6 better than MiMo-V2-Pro?
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 43.0 on the Noometry Index. MiMo-V2-Pro costs 11× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 4.6 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 4.6 lists at $3 and $15.
Is Claude Sonnet 4.6 or MiMo-V2-Pro better for coding?
Claude Sonnet 4.6 scores higher on coding benchmarks: 46.3 versus 43.8 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Pro does, with 1.05M tokens against 1M.
How many benchmarks do Claude Sonnet 4.6 and MiMo-V2-Pro share?
21 benchmarks have published results for both models. Claude Sonnet 4.6 has 57 scored results on Noometry and MiMo-V2-Pro has 23.