Model comparison
DeepSeek V4.1 Flash vs MiMo-V2-Omni
DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 43.6 on the Noometry Index.
Last verified . 18 shared benchmarks.
DeepSeekSummary
- They share 18 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 9 categories and MiMo-V2-Omni in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek V4.1 Flash leads 66.7 to 39.1.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.15 / $0.60 for DeepSeek V4.1 Flash.
- DeepSeek V4.1 Flash accepts more context: 1M tokens versus 262K.
- DeepSeek V4.1 Flash has downloadable open weights; the other is API-only.
Side by side
| DeepSeek V4.1 Flash | MiMo-V2-Omni | |
|---|---|---|
| Provider | DeepSeek | Xiaomi |
| Noometry Index | 52.8 | 43.6 |
| Released | 2026-09-09 | 2026-03-18 |
| Weights | Open | Proprietary |
| Context window | 1M | 262K |
| Max output | 393K | 131K |
| Input $ / M tokens | $0.15 | $0.14 |
| Output $ / M tokens | $0.60 | $0.28 |
| Results tracked | 37 | 18 |
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Category by category
Coding DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 52.9 (#32), MiMo-V2-Omni: 43.3 (#89)
| Benchmark | DeepSeek V4.1 Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1506 | 1466 |
| LMArena WebDev | 1619 | — |
| SciCode | 51.9% | — |
| ALE-Bench | 1,092 | — |
Agentic & Tool Use Not comparable
DeepSeek V4.1 Flash: 31.2 (#69), MiMo-V2-Omni: —
| Benchmark | DeepSeek V4.1 Flash | MiMo-V2-Omni |
|---|---|---|
| APEX-Agents | 39.5% | — |
| GDP.pdf | 19.8% | — |
Reasoning DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 50.2 (#36), MiMo-V2-Omni: 29.7 (#88)
| Benchmark | DeepSeek V4.1 Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1483 | 1445 |
| NYT Connections (extended) | 89.6% | — |
| CritPt | 14.3% | — |
| Mystery Game Puzzles | 43% | — |
| DTBench | 89.9% | — |
| LMCA | 47% | — |
| Surface Evolver Bench | 46.3% | — |
| Epoch Capabilities Index | 154.9 | — |
Math DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 66.7 (#25), MiMo-V2-Omni: 39.1 (#115)
| Benchmark | DeepSeek V4.1 Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | 1477 | 1430 |
| FrontierMath (Tiers 1-3) | 67.4% | — |
| FrontierMath Tier 4 | 26.8% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 54% | — |
Knowledge DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 57.9 (#38), MiMo-V2-Omni: 40.5 (#118)
| Benchmark | DeepSeek V4.1 Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1506 | 1449 |
| GPQA Diamond | 89.8% | — |
Multimodal Too close to call
DeepSeek V4.1 Flash: 39.1 (#61), MiMo-V2-Omni: 38.6 (#63)
| Benchmark | DeepSeek V4.1 Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | 1277 | 1228 |
| Furniture Assembly | 34.2% | — |
Multilingual DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 55.0 (#35), MiMo-V2-Omni: 51.8 (#102)
| Benchmark | DeepSeek V4.1 Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1448 | 1404 |
| LMArena Chinese | 1497 | 1465 |
| LMArena French | 1452 | 1447 |
| LMArena German | 1484 | 1399 |
| LMArena Japanese | 1412 | 1317 |
| LMArena Korean | 1452 | 1355 |
| LMArena Russian | 1471 | 1412 |
| LMArena Spanish | 1459 | 1434 |
Instruction Following DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 77.3 (#26), MiMo-V2-Omni: 75.2 (#66)
| Benchmark | DeepSeek V4.1 Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1474 | 1428 |
Long Context DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 45.2 (#47), MiMo-V2-Omni: 44.1 (#76)
| Benchmark | DeepSeek V4.1 Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1475 | 1442 |
Writing & Preference DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 65.4 (#48), MiMo-V2-Omni: 61.4 (#87)
| Benchmark | DeepSeek V4.1 Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1462 | 1423 |
| LMArena Creative Writing | 1435 | 1392 |
| LMArena Multi-Turn | 1457 | 1445 |
| EQ-Bench Creative Writing | 1540 | — |
Frequently asked questions
Is DeepSeek V4.1 Flash better than MiMo-V2-Omni?
DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 43.6 on the Noometry Index.
Which is cheaper, DeepSeek V4.1 Flash 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 V4.1 Flash lists at $0.15 and $0.60.
Is DeepSeek V4.1 Flash or MiMo-V2-Omni better for coding?
DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.9 versus 43.3 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4.1 Flash does, with 1M tokens against 262K.
How many benchmarks do DeepSeek V4.1 Flash and MiMo-V2-Omni share?
18 benchmarks have published results for both models. DeepSeek V4.1 Flash has 37 scored results on Noometry and MiMo-V2-Omni has 18.