Model comparison
MiMo-V2-Omni vs Qwen3.7 Max
Qwen3.7 Max is the stronger model overall, scoring 51.4 to 42.9 on the Noometry Index. MiMo-V2-Omni costs 21× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.
Last verified . 12 shared benchmarks.
Alibaba (Qwen)Summary
- They share 12 benchmarks with published results for both. MiMo-V2-Omni scores higher in 0 categories and Qwen3.7 Max in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.7 Max leads 62.3 to 36.4.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
- Qwen3.7 Max accepts more context: 1M tokens versus 262K.
Side by side
| MiMo-V2-Omni | Qwen3.7 Max | |
|---|---|---|
| Provider | Xiaomi | Alibaba (Qwen) |
| Noometry Index | 42.9 | 51.4 |
| Released | 2026-03-18 | 2026-05-19 |
| Weights | Proprietary | Proprietary |
| Context window | 262K | 1M |
| Max output | 131K | 131K |
| Input $ / M tokens | $0.14 | $2.50 |
| Output $ / M tokens | $0.28 | $7.50 |
| Results tracked | 18 | 33 |
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Category by category
Coding Qwen3.7 Max leads
MiMo-V2-Omni: 42.7 (#87), Qwen3.7 Max: 50.2 (#43)
| Benchmark | MiMo-V2-Omni | Qwen3.7 Max |
|---|---|---|
| LMArena Coding | 1467 | 1498 |
| SWE-bench Verified | — | 77.3% |
| LMArena WebDev | — | 1515 |
| SciCode | — | 48.8% |
| ALE-Bench | — | 1,189 |
Agentic & Tool Use Not comparable
MiMo-V2-Omni: —, Qwen3.7 Max: 21.8 (#129)
| Benchmark | MiMo-V2-Omni | Qwen3.7 Max |
|---|---|---|
| GBAEval | — | 0.4% |
Reasoning Qwen3.7 Max leads
MiMo-V2-Omni: 28.6 (#86), Qwen3.7 Max: 48.4 (#36)
| Benchmark | MiMo-V2-Omni | Qwen3.7 Max |
|---|---|---|
| LMArena Hard Prompts | 1445 | 1483 |
| SimpleBench | — | 70.4% |
| NYT Connections (extended) | — | 85.1% |
| CritPt | — | 13.4% |
| Chess Puzzles | — | 19% |
| EBR-Bench | — | 9.5% |
| Mystery Game Puzzles | — | 32% |
| DTBench | — | 92.3% |
| LMCA | — | 44% |
| Epoch Capabilities Index | — | 153.74 |
Math Qwen3.7 Max leads
MiMo-V2-Omni: 36.4 (#112), Qwen3.7 Max: 62.3 (#26)
| Benchmark | MiMo-V2-Omni | Qwen3.7 Max |
|---|---|---|
| LMArena Math | 1432 | 1488 |
| FrontierMath (Tiers 1-3) | — | 64.6% |
| FrontierMath Tier 4 | — | 34.1% |
| OTIS Mock AIME 2024-2025 | — | 95.6% |
| ProofBench | — | 26% |
Knowledge Qwen3.7 Max leads
MiMo-V2-Omni: 39.9 (#114), Qwen3.7 Max: 61.7 (#24)
| Benchmark | MiMo-V2-Omni | Qwen3.7 Max |
|---|---|---|
| LMArena Expert | 1449 | 1488 |
| GPQA Diamond | — | 90.9% |
| SimpleQA Verified | — | 55.8% |
Multimodal Not comparable
MiMo-V2-Omni: 37.9 (#62), Qwen3.7 Max: —
| Benchmark | MiMo-V2-Omni | Qwen3.7 Max |
|---|---|---|
| LMArena Vision | 1228 | — |
Multilingual Qwen3.7 Max leads
MiMo-V2-Omni: 52.0 (#97), Qwen3.7 Max: 57.1 (#13)
| Benchmark | MiMo-V2-Omni | Qwen3.7 Max |
|---|---|---|
| LMArena Non-English | 1404 | 1475 |
| LMArena Chinese | 1469 | 1533 |
| LMArena Russian | 1412 | 1482 |
| LMArena French | 1448 | — |
| LMArena German | 1398 | — |
| LMArena Japanese | 1318 | — |
| LMArena Korean | 1355 | — |
| LMArena Spanish | 1432 | — |
Instruction Following Qwen3.7 Max leads
MiMo-V2-Omni: 75.4 (#62), Qwen3.7 Max: 76.9 (#34)
| Benchmark | MiMo-V2-Omni | Qwen3.7 Max |
|---|---|---|
| LMArena Instruction Following | 1428 | 1460 |
Long Context Qwen3.7 Max leads
MiMo-V2-Omni: 44.1 (#72), Qwen3.7 Max: 45.4 (#34)
| Benchmark | MiMo-V2-Omni | Qwen3.7 Max |
|---|---|---|
| LMArena Longer Query | 1442 | 1484 |
Writing & Preference Qwen3.7 Max leads
MiMo-V2-Omni: 61.6 (#83), Qwen3.7 Max: 65.2 (#52)
| Benchmark | MiMo-V2-Omni | Qwen3.7 Max |
|---|---|---|
| LMArena Text | 1424 | 1476 |
| LMArena Creative Writing | 1393 | 1450 |
| LMArena Multi-Turn | 1446 | 1482 |
| EQ-Bench 4 | — | 1110 |
Frequently asked questions
Is MiMo-V2-Omni better than Qwen3.7 Max?
Qwen3.7 Max is the stronger model overall, scoring 51.4 to 42.9 on the Noometry Index. MiMo-V2-Omni costs 21× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.
Which is cheaper, MiMo-V2-Omni or Qwen3.7 Max?
MiMo-V2-Omni is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.
Is MiMo-V2-Omni or Qwen3.7 Max better for coding?
Qwen3.7 Max scores higher on coding benchmarks: 50.2 versus 42.7 in the Noometry coding category.
Which has the bigger context window?
Qwen3.7 Max does, with 1M tokens against 262K.
How many benchmarks do MiMo-V2-Omni and Qwen3.7 Max share?
12 benchmarks have published results for both models. MiMo-V2-Omni has 18 scored results on Noometry and Qwen3.7 Max has 33.