Model comparison
MiMo-V2-Omni vs Qwen3 Coder Next
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 34.3 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in reasoning, where MiMo-V2-Omni leads 29.7 to 22.4.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.12 / $0.80 for Qwen3 Coder Next.
- Qwen3 Coder Next has downloadable open weights; the other is API-only.
Side by side
| MiMo-V2-Omni | Qwen3 Coder Next | |
|---|---|---|
| Provider | Xiaomi | Alibaba (Qwen) |
| Noometry Index | 43.6 | 34.3 |
| Released | 2026-03-18 | 2026-02-02 |
| Weights | Proprietary | Open |
| Context window | 262K | 262K |
| Max output | 131K | 66K |
| Input $ / M tokens | $0.14 | $0.12 |
| Output $ / M tokens | $0.28 | $0.80 |
| Results tracked | 18 | 3 |
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Category by category
Coding MiMo-V2-Omni leads
MiMo-V2-Omni: 43.3 (#89), Qwen3 Coder Next: 36.3 (#210)
| Benchmark | MiMo-V2-Omni | Qwen3 Coder Next |
|---|---|---|
| SciCode | — | 32.3% |
| WeirdML | — | 34.4% |
| LMArena Coding | 1466 | — |
Reasoning MiMo-V2-Omni leads
MiMo-V2-Omni: 29.7 (#88), Qwen3 Coder Next: 22.4 (#196)
| Benchmark | MiMo-V2-Omni | Qwen3 Coder Next |
|---|---|---|
| CritPt | — | 0% |
| LMArena Hard Prompts | 1445 | — |
Math Not comparable
MiMo-V2-Omni: 39.1 (#115), Qwen3 Coder Next: —
| Benchmark | MiMo-V2-Omni | Qwen3 Coder Next |
|---|---|---|
| LMArena Math | 1430 | — |
Knowledge Not comparable
MiMo-V2-Omni: 40.5 (#118), Qwen3 Coder Next: —
| Benchmark | MiMo-V2-Omni | Qwen3 Coder Next |
|---|---|---|
| LMArena Expert | 1449 | — |
Multimodal Not comparable
MiMo-V2-Omni: 38.6 (#63), Qwen3 Coder Next: —
| Benchmark | MiMo-V2-Omni | Qwen3 Coder Next |
|---|---|---|
| LMArena Vision | 1228 | — |
Multilingual Not comparable
MiMo-V2-Omni: 51.8 (#102), Qwen3 Coder Next: —
| Benchmark | MiMo-V2-Omni | Qwen3 Coder Next |
|---|---|---|
| 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 Coder Next: —
| Benchmark | MiMo-V2-Omni | Qwen3 Coder Next |
|---|---|---|
| LMArena Instruction Following | 1428 | — |
Long Context Not comparable
MiMo-V2-Omni: 44.1 (#76), Qwen3 Coder Next: —
| Benchmark | MiMo-V2-Omni | Qwen3 Coder Next |
|---|---|---|
| LMArena Longer Query | 1442 | — |
Writing & Preference Not comparable
MiMo-V2-Omni: 61.4 (#87), Qwen3 Coder Next: —
| Benchmark | MiMo-V2-Omni | Qwen3 Coder Next |
|---|---|---|
| LMArena Text | 1423 | — |
| LMArena Creative Writing | 1392 | — |
| LMArena Multi-Turn | 1445 | — |
Frequently asked questions
Is MiMo-V2-Omni better than Qwen3 Coder Next?
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 34.3 on the Noometry Index.
Which is cheaper, MiMo-V2-Omni or Qwen3 Coder Next?
MiMo-V2-Omni is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Qwen3 Coder Next lists at $0.12 and $0.80.
Is MiMo-V2-Omni or Qwen3 Coder Next better for coding?
MiMo-V2-Omni scores higher on coding benchmarks: 43.3 versus 36.3 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do MiMo-V2-Omni and Qwen3 Coder Next share?
0 benchmarks have published results for both models. MiMo-V2-Omni has 18 scored results on Noometry and Qwen3 Coder Next has 3.