Model comparison
DeepSeek-V3.2-Speciale vs MiMo-V2-Flash
MiMo-V2-Flash is the stronger model overall, scoring 41.3 to 39.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in writing & preference, where MiMo-V2-Flash leads 59.7 to 46.0.
- MiMo-V2-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
- MiMo-V2-Flash accepts more context: 262K tokens versus 128K.
Side by side
| DeepSeek-V3.2-Speciale | MiMo-V2-Flash | |
|---|---|---|
| Provider | DeepSeek | Xiaomi |
| Noometry Index | 39.7 | 41.3 |
| Released | 2025-12-01 | 2025-12-16 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.58 | $0.14 |
| Output $ / M tokens | $1.68 | $0.28 |
| Results tracked | 3 | 21 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 40.4 (#140), MiMo-V2-Flash: 36.1 (#211)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Flash |
|---|---|---|
| LMArena WebDev | — | 1330 |
| SciCode | — | 25.9% |
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1443 |
| ALE-Bench | — | 737.95 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), MiMo-V2-Flash: 24.9 (#157)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Flash |
|---|---|---|
| SimpleBench | 52.6% | — |
| CritPt | — | 0% |
| LMArena Hard Prompts | — | 1420 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Flash: 38.3 (#139)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Flash |
|---|---|---|
| LMArena Math | — | 1396 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Flash: 39.7 (#131)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Flash |
|---|---|---|
| LMArena Expert | — | 1425 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Flash: 51.0 (#113)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Flash |
|---|---|---|
| LMArena Non-English | — | 1392 |
| LMArena Chinese | — | 1462 |
| LMArena French | — | 1429 |
| LMArena German | — | 1395 |
| LMArena Japanese | — | 1325 |
| LMArena Korean | — | 1358 |
| LMArena Russian | — | 1387 |
| LMArena Spanish | — | 1420 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Flash: 73.5 (#120)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Flash |
|---|---|---|
| LMArena Instruction Following | — | 1392 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Flash: 43.0 (#110)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Flash |
|---|---|---|
| LMArena Longer Query | — | 1409 |
Writing & Preference MiMo-V2-Flash leads
DeepSeek-V3.2-Speciale: 46.0 (#222), MiMo-V2-Flash: 59.7 (#106)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Flash |
|---|---|---|
| LMArena Text | — | 1411 |
| LMArena Creative Writing | — | 1375 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1404 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than MiMo-V2-Flash?
MiMo-V2-Flash is the stronger model overall, scoring 41.3 to 39.7 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or MiMo-V2-Flash?
MiMo-V2-Flash 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-Flash better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 36.1 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Flash does, with 262K tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and MiMo-V2-Flash share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and MiMo-V2-Flash has 21.