Model comparison
DeepSeek-V3.2-Speciale vs MiMo-V2-Pro
MiMo-V2-Pro is the stronger model overall, scoring 42.4 to 39.1 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeekSummary
- The widest gap is in writing & preference, where MiMo-V2-Pro leads 62.9 to 46.1.
- MiMo-V2-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-Pro accepts more context: 1.05M tokens versus 128K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.2-Speciale | MiMo-V2-Pro | |
|---|---|---|
| Provider | DeepSeek | Xiaomi |
| Noometry Index | 39.1 | 42.4 |
| Released | 2025-12-01 | 2026-03-18 |
| Weights | Open | Proprietary |
| 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 | 23 |
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Category by category
Coding MiMo-V2-Pro leads
DeepSeek-V3.2-Speciale: 39.9 (#136), MiMo-V2-Pro: 43.4 (#76)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Pro |
|---|---|---|
| LMArena WebDev | — | 1433 |
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1476 |
| ALE-Bench | — | 785.17 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.1 (#65), MiMo-V2-Pro: 21.3 (#200)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Pro |
|---|---|---|
| SimpleBench | 52.6% | — |
| NYT Connections (extended) | — | 25.8% |
| Thematic Generalization | — | 45.9% |
| LMArena Hard Prompts | — | 1457 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Pro: 36.7 (#104)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | — | 1447 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Pro: 40.8 (#106)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | — | 1479 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Pro: 52.9 (#77)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | — | 1416 |
| LMArena Chinese | — | 1455 |
| LMArena French | — | 1470 |
| LMArena German | — | 1417 |
| LMArena Japanese | — | 1366 |
| LMArena Korean | — | 1401 |
| LMArena Russian | — | 1427 |
| LMArena Spanish | — | 1458 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Pro: 76.2 (#46)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | — | 1444 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Pro: 41.5 (#133)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Pro |
|---|---|---|
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |
| LMArena Longer Query | — | 1455 |
Writing & Preference MiMo-V2-Pro leads
DeepSeek-V3.2-Speciale: 46.1 (#217), MiMo-V2-Pro: 62.9 (#67)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | — | 1436 |
| LMArena Creative Writing | — | 1415 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1456 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than MiMo-V2-Pro?
MiMo-V2-Pro is the stronger model overall, scoring 42.4 to 39.1 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or MiMo-V2-Pro?
MiMo-V2-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-Pro better for coding?
MiMo-V2-Pro scores higher on coding benchmarks: 43.4 versus 39.9 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Pro does, with 1.05M tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and MiMo-V2-Pro share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and MiMo-V2-Pro has 23.