Model comparison
DeepSeek-V3.2-Speciale vs MiMo-V2-Omni
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 39.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeekSummary
- The widest gap is in writing & preference, where MiMo-V2-Omni leads 61.4 to 46.0.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
- MiMo-V2-Omni accepts more context: 262K 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-Omni | |
|---|---|---|
| Provider | DeepSeek | Xiaomi |
| Noometry Index | 39.7 | 43.6 |
| Released | 2025-12-01 | 2026-03-18 |
| Weights | Open | Proprietary |
| Context window | 128K | 262K |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.58 | $0.14 |
| Output $ / M tokens | $1.68 | $0.28 |
| Results tracked | 3 | 18 |
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Category by category
Coding MiMo-V2-Omni leads
DeepSeek-V3.2-Speciale: 40.4 (#140), MiMo-V2-Omni: 43.3 (#89)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Omni |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1466 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), MiMo-V2-Omni: 29.7 (#88)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Omni |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 1445 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Omni: 39.1 (#115)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | — | 1430 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Omni: 40.5 (#118)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | — | 1449 |
Multimodal Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Omni: 38.6 (#63)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | — | 1228 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Omni: 51.8 (#102)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | — | 1404 |
| LMArena Chinese | — | 1465 |
| LMArena French | — | 1447 |
| LMArena German | — | 1399 |
| LMArena Japanese | — | 1317 |
| LMArena Korean | — | 1355 |
| LMArena Russian | — | 1412 |
| LMArena Spanish | — | 1434 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Omni: 75.2 (#66)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | — | 1428 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, MiMo-V2-Omni: 44.1 (#76)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | — | 1442 |
Writing & Preference MiMo-V2-Omni leads
DeepSeek-V3.2-Speciale: 46.0 (#222), MiMo-V2-Omni: 61.4 (#87)
| Benchmark | DeepSeek-V3.2-Speciale | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | — | 1423 |
| LMArena Creative Writing | — | 1392 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1445 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than MiMo-V2-Omni?
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 39.7 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or MiMo-V2-Omni?
MiMo-V2-Omni 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-Omni better for coding?
MiMo-V2-Omni scores higher on coding benchmarks: 43.3 versus 40.4 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Omni does, with 262K tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and MiMo-V2-Omni share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and MiMo-V2-Omni has 18.