Model comparison
MiMo-V2-Pro vs Qwen1.5-7B
MiMo-V2-Pro is the stronger model overall, scoring 42.4 to 30.8 on the Noometry Index.
Last verified . 12 shared benchmarks.
Alibaba (Qwen)Summary
- They share 12 benchmarks with published results for both. MiMo-V2-Pro scores higher in 8 categories and Qwen1.5-7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2-Pro leads 62.9 to 29.8.
- Qwen1.5-7B has downloadable open weights; the other is API-only.
Side by side
| MiMo-V2-Pro | Qwen1.5-7B | |
|---|---|---|
| Provider | Xiaomi | Alibaba (Qwen) |
| Noometry Index | 42.4 | 30.8 |
| Released | 2026-03-18 | 2024-02-04 |
| Weights | Proprietary | Open |
| Context window | 1.05M | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.43 | — |
| Output $ / M tokens | $0.87 | — |
| Results tracked | 23 | 13 |
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Category by category
Coding MiMo-V2-Pro leads
MiMo-V2-Pro: 43.4 (#76), Qwen1.5-7B: 31.6 (#271)
| Benchmark | MiMo-V2-Pro | Qwen1.5-7B |
|---|---|---|
| LMArena Coding | 1476 | 1107 |
| LMArena WebDev | 1433 | — |
| ALE-Bench | 785.17 | — |
Reasoning MiMo-V2-Pro leads
MiMo-V2-Pro: 21.3 (#200), Qwen1.5-7B: 19.5 (#237)
| Benchmark | MiMo-V2-Pro | Qwen1.5-7B |
|---|---|---|
| LMArena Hard Prompts | 1457 | 1066 |
| NYT Connections (extended) | 25.8% | — |
| Thematic Generalization | 45.9% | — |
Math MiMo-V2-Pro leads
MiMo-V2-Pro: 36.7 (#104), Qwen1.5-7B: 29.0 (#222)
| Benchmark | MiMo-V2-Pro | Qwen1.5-7B |
|---|---|---|
| LMArena Math | 1447 | 1080 |
Knowledge MiMo-V2-Pro leads
MiMo-V2-Pro: 40.8 (#106), Qwen1.5-7B: 28.2 (#239)
| Benchmark | MiMo-V2-Pro | Qwen1.5-7B |
|---|---|---|
| LMArena Expert | 1479 | 1055 |
| MMLU | — | 62.6% |
Multilingual MiMo-V2-Pro leads
MiMo-V2-Pro: 52.9 (#77), Qwen1.5-7B: 28.6 (#266)
| Benchmark | MiMo-V2-Pro | Qwen1.5-7B |
|---|---|---|
| LMArena Non-English | 1416 | 1058 |
| LMArena Chinese | 1455 | 1140 |
| LMArena Russian | 1427 | 1006 |
| LMArena French | 1470 | — |
| LMArena German | 1417 | — |
| LMArena Japanese | 1366 | — |
| LMArena Korean | 1401 | — |
| LMArena Spanish | 1458 | — |
Instruction Following MiMo-V2-Pro leads
MiMo-V2-Pro: 76.2 (#46), Qwen1.5-7B: 54.4 (#276)
| Benchmark | MiMo-V2-Pro | Qwen1.5-7B |
|---|---|---|
| LMArena Instruction Following | 1444 | 1058 |
Long Context MiMo-V2-Pro leads
MiMo-V2-Pro: 41.5 (#133), Qwen1.5-7B: 33.1 (#261)
| Benchmark | MiMo-V2-Pro | Qwen1.5-7B |
|---|---|---|
| LMArena Longer Query | 1455 | 1090 |
| CL-bench | 15.7% | — |
| CL-bench Life | 6.9% | — |
Writing & Preference MiMo-V2-Pro leads
MiMo-V2-Pro: 62.9 (#67), Qwen1.5-7B: 29.8 (#288)
| Benchmark | MiMo-V2-Pro | Qwen1.5-7B |
|---|---|---|
| LMArena Text | 1436 | 1084 |
| LMArena Creative Writing | 1415 | 1035 |
| LMArena Multi-Turn | 1456 | 1061 |
Frequently asked questions
Is MiMo-V2-Pro better than Qwen1.5-7B?
MiMo-V2-Pro is the stronger model overall, scoring 42.4 to 30.8 on the Noometry Index.
Is MiMo-V2-Pro or Qwen1.5-7B better for coding?
MiMo-V2-Pro scores higher on coding benchmarks: 43.4 versus 31.6 in the Noometry coding category.
How many benchmarks do MiMo-V2-Pro and Qwen1.5-7B share?
12 benchmarks have published results for both models. MiMo-V2-Pro has 23 scored results on Noometry and Qwen1.5-7B has 13.