Model comparison
MiMo-V2.6-Flash vs Qwen3 235B-A22B
MiMo-V2.6-Flash is the stronger model overall, scoring 48.5 to 43.5 on the Noometry Index.
Last verified . 16 shared benchmarks.
Alibaba (Qwen)Summary
- They share 16 benchmarks with published results for both. MiMo-V2.6-Flash scores higher in 6 categories and Qwen3 235B-A22B in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where MiMo-V2.6-Flash leads 36.5 to 15.7.
- The biggest single-benchmark swing is CritPt: 12% for MiMo-V2.6-Flash and 0% for Qwen3 235B-A22B.
- MiMo-V2.6-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.70 / $2.80 for Qwen3 235B-A22B.
- MiMo-V2.6-Flash accepts more context: 1.05M tokens versus 131K.
Side by side
| MiMo-V2.6-Flash | Qwen3 235B-A22B | |
|---|---|---|
| Provider | Xiaomi | Alibaba (Qwen) |
| Noometry Index | 48.5 | 43.5 |
| Released | 2026-09-21 | 2025-04 |
| Weights | Open | Open |
| Context window | 1.05M | 131K |
| Max output | 131K | 16K |
| Input $ / M tokens | $0.14 | $0.70 |
| Output $ / M tokens | $0.28 | $2.80 |
| Results tracked | 19 | 49 |
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Category by category
Coding MiMo-V2.6-Flash leads
MiMo-V2.6-Flash: 53.4 (#30), Qwen3 235B-A22B: 44.3 (#75)
| Benchmark | MiMo-V2.6-Flash | Qwen3 235B-A22B |
|---|---|---|
| SciCode | 51.3% | 42.4% |
| LMArena Coding | 1504 | 1445 |
| Aider Polyglot | — | 59.6% |
| LMArena WebDev | 1637 | — |
| WeirdML | — | 41% |
Agentic & Tool Use Not comparable
MiMo-V2.6-Flash: —, Qwen3 235B-A22B: 33.9 (#51)
| Benchmark | MiMo-V2.6-Flash | Qwen3 235B-A22B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 52.1% |
| Vending-Bench 2 | — | -11.34 |
Reasoning MiMo-V2.6-Flash leads
MiMo-V2.6-Flash: 36.5 (#66), Qwen3 235B-A22B: 15.7 (#311)
| Benchmark | MiMo-V2.6-Flash | Qwen3 235B-A22B |
|---|---|---|
| CritPt | 12% | 0% |
| LMArena Hard Prompts | 1482 | 1433 |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 31% |
| Kagi LLM Benchmark | — | 69.4% |
| ARC-AGI-1 | — | 11% |
| Chess Puzzles | — | 12% |
| Mystery Game Puzzles | — | 9% |
| DTBench | — | 80.3% |
| LMCA | — | 29.3% |
| Epoch Capabilities Index | — | 143.85 |
| ForecastBench | — | 59.7 |
Math MiMo-V2.6-Flash leads
MiMo-V2.6-Flash: 51.9 (#52), Qwen3 235B-A22B: 50.4 (#57)
| Benchmark | MiMo-V2.6-Flash | Qwen3 235B-A22B |
|---|---|---|
| LMArena Math | 1468 | 1432 |
| OTIS Mock AIME 2024-2025 | — | 86.7% |
| ProofBench | 63% | — |
| Omni-MATH | — | 71.8% |
| MATH Level 5 | — | 68.9% |
| FrontierMath (Feb 2025 set) | — | 8.5% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Qwen3 235B-A22B leads
MiMo-V2.6-Flash: 42.2 (#99), Qwen3 235B-A22B: 49.6 (#73)
| Benchmark | MiMo-V2.6-Flash | Qwen3 235B-A22B |
|---|---|---|
| LMArena Expert | 1501 | 1463 |
| GPQA Diamond | — | 80.1% |
| SimpleQA Verified | — | 40.4% |
| MMLU-Pro | — | 84.4% |
| Confabulations | — | 15.6% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 72.7% |
Multimodal Not comparable
MiMo-V2.6-Flash: 40.5 (#47), Qwen3 235B-A22B: —
| Benchmark | MiMo-V2.6-Flash | Qwen3 235B-A22B |
|---|---|---|
| LMArena Vision | 1259 | — |
Multilingual MiMo-V2.6-Flash leads
MiMo-V2.6-Flash: 54.0 (#51), Qwen3 235B-A22B: 52.3 (#89)
| Benchmark | MiMo-V2.6-Flash | Qwen3 235B-A22B |
|---|---|---|
| LMArena Non-English | 1434 | 1409 |
| LMArena Chinese | 1511 | 1481 |
| LMArena French | 1475 | 1445 |
| LMArena Russian | 1409 | 1411 |
| LMArena Spanish | 1456 | 1430 |
| LMArena German | — | 1433 |
| LMArena Japanese | — | 1399 |
| LMArena Korean | — | 1391 |
Instruction Following MiMo-V2.6-Flash leads
MiMo-V2.6-Flash: 76.8 (#35), Qwen3 235B-A22B: 72.6 (#136)
| Benchmark | MiMo-V2.6-Flash | Qwen3 235B-A22B |
|---|---|---|
| LMArena Instruction Following | 1463 | 1408 |
| IFEval | — | 83.5% |
Long Context Qwen3 235B-A22B leads
MiMo-V2.6-Flash: 44.8 (#57), Qwen3 235B-A22B: 46.1 (#26)
| Benchmark | MiMo-V2.6-Flash | Qwen3 235B-A22B |
|---|---|---|
| LMArena Longer Query | 1463 | 1426 |
| Fiction.LiveBench | — | 75% |
Writing & Preference MiMo-V2.6-Flash leads
MiMo-V2.6-Flash: 63.1 (#67), Qwen3 235B-A22B: 59.6 (#108)
| Benchmark | MiMo-V2.6-Flash | Qwen3 235B-A22B |
|---|---|---|
| LMArena Text | 1455 | 1419 |
| LMArena Creative Writing | 1400 | 1384 |
| LMArena Multi-Turn | 1451 | 1432 |
| Short-Story Creative Writing | — | 83% |
| EQ-Bench Creative Writing | — | 1366 |
| WildBench | — | 86.6% |
Frequently asked questions
Is MiMo-V2.6-Flash better than Qwen3 235B-A22B?
MiMo-V2.6-Flash is the stronger model overall, scoring 48.5 to 43.5 on the Noometry Index.
Which is cheaper, MiMo-V2.6-Flash or Qwen3 235B-A22B?
MiMo-V2.6-Flash is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Qwen3 235B-A22B lists at $0.70 and $2.80.
Is MiMo-V2.6-Flash or Qwen3 235B-A22B better for coding?
MiMo-V2.6-Flash scores higher on coding benchmarks: 53.4 versus 44.3 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.6-Flash does, with 1.05M tokens against 131K.
How many benchmarks do MiMo-V2.6-Flash and Qwen3 235B-A22B share?
16 benchmarks have published results for both models. MiMo-V2.6-Flash has 19 scored results on Noometry and Qwen3 235B-A22B has 49.