Model comparison
DeepSeek-V3.2-Speciale vs MiMo-V2.5-Pro
MiMo-V2.5-Pro is the stronger model overall, scoring 44.8 to 39.1 on the Noometry Index.
Last verified . 1 shared benchmarks.
DeepSeekSummary
- They share 1 benchmark with published results for both. DeepSeek-V3.2-Speciale scores higher in 1 category and MiMo-V2.5-Pro in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2.5-Pro leads 65.5 to 46.1.
- MiMo-V2.5-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
- MiMo-V2.5-Pro accepts more context: 1.05M tokens versus 128K.
Side by side
| DeepSeek-V3.2-Speciale | MiMo-V2.5-Pro | |
|---|---|---|
| Provider | DeepSeek | Xiaomi |
| Noometry Index | 39.1 | 44.8 |
| Released | 2025-12-01 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 128K | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.58 | $0.43 |
| Output $ / M tokens | $1.68 | $0.87 |
| Results tracked | 3 | 27 |
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Category by category
Coding MiMo-V2.5-Pro leads
DeepSeek-V3.2-Speciale: 39.9 (#136), MiMo-V2.5-Pro: 47.0 (#58)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5-Pro |
|---|---|---|
| LMArena WebDev | — | 1477 |
| SciCode | — | 50.2% |
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1502 |
| ALE-Bench | — | 899.8 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.1 (#65), MiMo-V2.5-Pro: 25.9 (#124)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5-Pro |
|---|---|---|
| SimpleBench | 52.6% | — |
| NYT Connections (extended) | — | 34.4% |
| CritPt | — | 4% |
| LMArena Hard Prompts | — | 1487 |
| DTBench | — | 84.5% |
| LMCA | — | 29.5% |
Math Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2.5-Pro: 38.6 (#84)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5-Pro |
|---|---|---|
| ProofBench | — | 22% |
| LMArena Math | — | 1480 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2.5-Pro: 41.5 (#100)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Expert | — | 1501 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2.5-Pro: 55.3 (#33)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Non-English | — | 1449 |
| LMArena Chinese | — | 1507 |
| LMArena French | — | 1489 |
| LMArena German | — | 1455 |
| LMArena Japanese | — | 1418 |
| LMArena Korean | — | 1436 |
| LMArena Russian | — | 1450 |
| LMArena Spanish | — | 1470 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2.5-Pro: 77.6 (#21)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Instruction Following | — | 1477 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2.5-Pro: 45.4 (#38)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Longer Query | — | 1482 |
Writing & Preference MiMo-V2.5-Pro leads
DeepSeek-V3.2-Speciale: 46.1 (#217), MiMo-V2.5-Pro: 65.5 (#47)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2.5-Pro |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 1493 |
| LMArena Text | — | 1465 |
| LMArena Creative Writing | — | 1440 |
| EQ-Bench 4 | — | 1208 |
| LMArena Multi-Turn | — | 1477 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than MiMo-V2.5-Pro?
MiMo-V2.5-Pro is the stronger model overall, scoring 44.8 to 39.1 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or MiMo-V2.5-Pro?
MiMo-V2.5-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.
Is DeepSeek-V3.2-Speciale or MiMo-V2.5-Pro better for coding?
MiMo-V2.5-Pro scores higher on coding benchmarks: 47.0 versus 39.9 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.5-Pro does, with 1.05M tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and MiMo-V2.5-Pro share?
1 benchmark has published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and MiMo-V2.5-Pro has 27.