# DeepSeek-V3.2-Speciale vs MiMo-V2.5

> MiMo-V2.5 is the stronger model overall, scoring 43.0 to 39.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-speciale-vs-mimo-v2-5
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in writing & preference, where MiMo-V2.5 leads 61.8 to 46.1.
- MiMo-V2.5 is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
- MiMo-V2.5 accepts more context: 1.05M tokens versus 128K.

## Snapshot

| | DeepSeek-V3.2-Speciale | MiMo-V2.5 |
|---|---|---|
| Provider | DeepSeek | Xiaomi |
| Noometry Index | 39.1 | 43.0 |
| Rank | 159 | 89 |
| Context | 128K | 1.05M |
| Input $/M | $0.58 | $0.14 |
| Output $/M | $1.68 | $0.28 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.2-Speciale: 39.9 (#136)
- MiMo-V2.5: 43.6 (#75)

| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5 |
|---|---|---|
| LMArena WebDev | — | 1438 |
| SciCode | — | 43.1% |
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1469 |
| ALE-Bench | — | 513.95 |

## Reasoning

- DeepSeek-V3.2-Speciale: 32.1 (#65)
- MiMo-V2.5: 27.8 (#98)

| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5 |
|---|---|---|
| SimpleBench | 52.6% | — |
| CritPt | — | 3.7% |
| LMArena Hard Prompts | — | 1450 |

## Math

- DeepSeek-V3.2-Speciale: —
- MiMo-V2.5: 35.4 (#145)

| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5 |
|---|---|---|
| ProofBench | — | 16% |
| LMArena Math | — | 1436 |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- MiMo-V2.5: 40.2 (#109)

| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5 |
|---|---|---|
| LMArena Expert | — | 1459 |

## Multimodal

- DeepSeek-V3.2-Speciale: —
- MiMo-V2.5: 39.0 (#53)

| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5 |
|---|---|---|
| LMArena Vision | — | 1245 |

## Multilingual

- DeepSeek-V3.2-Speciale: —
- MiMo-V2.5: 52.0 (#96)

| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5 |
|---|---|---|
| LMArena Non-English | — | 1404 |
| LMArena Chinese | — | 1467 |
| LMArena French | — | 1447 |
| LMArena German | — | 1421 |
| LMArena Japanese | — | 1304 |
| LMArena Korean | — | 1363 |
| LMArena Russian | — | 1395 |
| LMArena Spanish | — | 1412 |

## Instruction Following

- DeepSeek-V3.2-Speciale: —
- MiMo-V2.5: 75.7 (#55)

| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5 |
|---|---|---|
| LMArena Instruction Following | — | 1433 |

## Long Context

- DeepSeek-V3.2-Speciale: —
- MiMo-V2.5: 44.1 (#69)

| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5 |
|---|---|---|
| LMArena Longer Query | — | 1444 |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.1 (#217)
- MiMo-V2.5: 61.8 (#82)

| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5 |
|---|---|---|
| LMArena Text | — | 1427 |
| LMArena Creative Writing | — | 1392 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1445 |

## FAQ

### Is DeepSeek-V3.2-Speciale better than MiMo-V2.5?

MiMo-V2.5 is the stronger model overall, scoring 43.0 to 39.1 on the Noometry Index.

### Which is cheaper, DeepSeek-V3.2-Speciale or MiMo-V2.5?

MiMo-V2.5 is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

### Is DeepSeek-V3.2-Speciale or MiMo-V2.5 better for coding?

MiMo-V2.5 scores higher on coding benchmarks: 43.6 versus 39.9 in the Noometry coding category.

### Which has the bigger context window?

MiMo-V2.5 does, with 1.05M tokens against 128K.

### How many benchmarks do DeepSeek-V3.2-Speciale and MiMo-V2.5 share?

0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and MiMo-V2.5 has 23.