# MiMo-V2-Pro vs Qwen3 32B

> MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 39.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/mimo-v2-pro-vs-qwen3-32b
- Last updated: 2026-10-10
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. MiMo-V2-Pro scores higher in 6 categories and Qwen3 32B in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2-Pro leads 62.8 to 52.9.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.70 / $2.80 for Qwen3 32B.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 131K.
- Qwen3 32B has downloadable open weights; the other is API-only.

## Snapshot

| | MiMo-V2-Pro | Qwen3 32B |
|---|---|---|
| Provider | Xiaomi | Alibaba (Qwen) |
| Noometry Index | 43.0 | 39.2 |
| Rank | 103 | 172 |
| Context | 1.05M | 131K |
| Input $/M | $0.43 | $0.70 |
| Output $/M | $0.87 | $2.80 |
| Weights | Proprietary | Open |

## Coding

- MiMo-V2-Pro: 43.8 (#83)
- Qwen3 32B: 37.7 (#190)

| Benchmark | MiMo-V2-Pro | Qwen3 32B |
|---|---|---|
| LMArena Coding | 1476 | 1358 |
| Aider Polyglot | — | 40% |
| LMArena WebDev | 1433 | — |
| SciCode | — | 35.4% |
| ALE-Bench | 785.17 | — |

## Agentic & Tool Use

- MiMo-V2-Pro: —
- Qwen3 32B: 32.6 (#62)

| Benchmark | MiMo-V2-Pro | Qwen3 32B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 48.7% |

## Reasoning

- MiMo-V2-Pro: 22.1 (#206)
- Qwen3 32B: 20.2 (#241)

| Benchmark | MiMo-V2-Pro | Qwen3 32B |
|---|---|---|
| LMArena Hard Prompts | 1457 | 1334 |
| Kagi LLM Benchmark | — | 54.9% |
| NYT Connections (extended) | 25.8% | — |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 5% |
| Thematic Generalization | 45.9% | — |
| DTBench | — | 67.5% |
| LMCA | — | 17.3% |
| Epoch Capabilities Index | — | 138.51 |

## Math

- MiMo-V2-Pro: 39.5 (#102)
- Qwen3 32B: 39.7 (#99)

| Benchmark | MiMo-V2-Pro | Qwen3 32B |
|---|---|---|
| LMArena Math | 1447 | 1399 |
| OTIS Mock AIME 2024-2025 | — | 66.9% |

## Knowledge

- MiMo-V2-Pro: 41.4 (#111)
- Qwen3 32B: 40.0 (#125)

| Benchmark | MiMo-V2-Pro | Qwen3 32B |
|---|---|---|
| LMArena Expert | 1478 | 1362 |
| GPQA Diamond | — | 65.7% |
| Vectara Hallucination Rate | — | 5.9% |

## Multilingual

- MiMo-V2-Pro: 52.7 (#81)
- Qwen3 32B: 45.6 (#167)

| Benchmark | MiMo-V2-Pro | Qwen3 32B |
|---|---|---|
| LMArena Non-English | 1416 | 1317 |
| LMArena Chinese | 1456 | 1357 |
| LMArena German | 1417 | 1341 |
| LMArena Russian | 1427 | 1311 |
| LMArena French | 1469 | — |
| LMArena Japanese | 1366 | — |
| LMArena Korean | 1400 | — |
| LMArena Spanish | 1457 | — |

## Instruction Following

- MiMo-V2-Pro: 76.0 (#49)
- Qwen3 32B: 68.9 (#179)

| Benchmark | MiMo-V2-Pro | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | 1445 | 1305 |

## Long Context

- MiMo-V2-Pro: 41.5 (#138)
- Qwen3 32B: 43.8 (#87)

| Benchmark | MiMo-V2-Pro | Qwen3 32B |
|---|---|---|
| LMArena Longer Query | 1455 | 1327 |
| Fiction.LiveBench | — | 74.2% |
| CL-bench | 15.7% | — |
| CL-bench Life | 6.9% | — |

## Writing & Preference

- MiMo-V2-Pro: 62.8 (#70)
- Qwen3 32B: 52.9 (#163)

| Benchmark | MiMo-V2-Pro | Qwen3 32B |
|---|---|---|
| LMArena Text | 1436 | 1340 |
| LMArena Creative Writing | 1415 | 1297 |
| LMArena Multi-Turn | 1456 | 1331 |

## FAQ

### Is MiMo-V2-Pro better than Qwen3 32B?

MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 39.2 on the Noometry Index.

### Which is cheaper, MiMo-V2-Pro or Qwen3 32B?

MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; Qwen3 32B lists at $0.70 and $2.80.

### Is MiMo-V2-Pro or Qwen3 32B better for coding?

MiMo-V2-Pro scores higher on coding benchmarks: 43.8 versus 37.7 in the Noometry coding category.

### Which has the bigger context window?

MiMo-V2-Pro does, with 1.05M tokens against 131K.

### How many benchmarks do MiMo-V2-Pro and Qwen3 32B share?

13 benchmarks have published results for both models. MiMo-V2-Pro has 23 scored results on Noometry and Qwen3 32B has 26.
