Model comparison
MiMo-V2-Omni vs Qwen3.6 27B
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 42.2 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 40.5.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.60 / $3.60 for Qwen3.6 27B.
- Qwen3.6 27B has downloadable open weights; the other is API-only.
Side by side
| MiMo-V2-Omni | Qwen3.6 27B | |
|---|---|---|
| Provider | Xiaomi | Alibaba (Qwen) |
| Noometry Index | 43.6 | 42.2 |
| Released | 2026-03-18 | 2026-04-22 |
| Weights | Proprietary | Open |
| Context window | 262K | 262K |
| Max output | 131K | 66K |
| Input $ / M tokens | $0.14 | $0.60 |
| Output $ / M tokens | $0.28 | $3.60 |
| Results tracked | 18 | 11 |
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Category by category
Coding MiMo-V2-Omni leads
MiMo-V2-Omni: 43.3 (#89), Qwen3.6 27B: 39.1 (#163)
| Benchmark | MiMo-V2-Omni | Qwen3.6 27B |
|---|---|---|
| SciCode | — | 37.3% |
| LMArena Coding | 1466 | — |
Reasoning MiMo-V2-Omni leads
MiMo-V2-Omni: 29.7 (#88), Qwen3.6 27B: 25.0 (#153)
| Benchmark | MiMo-V2-Omni | Qwen3.6 27B |
|---|---|---|
| CritPt | — | 0.9% |
| Chess Puzzles | — | 22% |
| LMArena Hard Prompts | 1445 | — |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 78.1% |
| LMCA | — | 34.5% |
| Epoch Capabilities Index | — | 146.5 |
Math Qwen3.6 27B leads
MiMo-V2-Omni: 39.1 (#115), Qwen3.6 27B: 48.5 (#62)
| Benchmark | MiMo-V2-Omni | Qwen3.6 27B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 35.1% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
| LMArena Math | 1430 | — |
Knowledge Qwen3.6 27B leads
MiMo-V2-Omni: 40.5 (#118), Qwen3.6 27B: 52.4 (#63)
| Benchmark | MiMo-V2-Omni | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | — | 85.9% |
| LMArena Expert | 1449 | — |
Multimodal Not comparable
MiMo-V2-Omni: 38.6 (#63), Qwen3.6 27B: —
| Benchmark | MiMo-V2-Omni | Qwen3.6 27B |
|---|---|---|
| LMArena Vision | 1228 | — |
Multilingual Not comparable
MiMo-V2-Omni: 51.8 (#102), Qwen3.6 27B: —
| Benchmark | MiMo-V2-Omni | Qwen3.6 27B |
|---|---|---|
| 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
MiMo-V2-Omni: 75.2 (#66), Qwen3.6 27B: —
| Benchmark | MiMo-V2-Omni | Qwen3.6 27B |
|---|---|---|
| LMArena Instruction Following | 1428 | — |
Long Context Not comparable
MiMo-V2-Omni: 44.1 (#76), Qwen3.6 27B: —
| Benchmark | MiMo-V2-Omni | Qwen3.6 27B |
|---|---|---|
| LMArena Longer Query | 1442 | — |
Writing & Preference MiMo-V2-Omni leads
MiMo-V2-Omni: 61.4 (#87), Qwen3.6 27B: 50.3 (#181)
| Benchmark | MiMo-V2-Omni | Qwen3.6 27B |
|---|---|---|
| LMArena Text | 1423 | — |
| LMArena Creative Writing | 1392 | — |
| EQ-Bench 4 | — | 1026 |
| LMArena Multi-Turn | 1445 | — |
Frequently asked questions
Is MiMo-V2-Omni better than Qwen3.6 27B?
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 42.2 on the Noometry Index.
Which is cheaper, MiMo-V2-Omni or Qwen3.6 27B?
MiMo-V2-Omni is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Qwen3.6 27B lists at $0.60 and $3.60.
Is MiMo-V2-Omni or Qwen3.6 27B better for coding?
MiMo-V2-Omni scores higher on coding benchmarks: 43.3 versus 39.1 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do MiMo-V2-Omni and Qwen3.6 27B share?
0 benchmarks have published results for both models. MiMo-V2-Omni has 18 scored results on Noometry and Qwen3.6 27B has 11.