Model comparison
MiMo-V2-Pro vs Qwen3 235B-A22B
MiMo-V2-Pro and Qwen3 235B-A22B score almost the same on the Noometry Index (43.0 vs 43.5), so choose on price, context window or the category you care about most.
Last verified . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. MiMo-V2-Pro scores higher in 4 categories and Qwen3 235B-A22B in 4 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3 235B-A22B leads 50.4 to 39.5.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.70 / $2.80 for Qwen3 235B-A22B.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 131K.
- Qwen3 235B-A22B has downloadable open weights; the other is API-only.
Side by side
| MiMo-V2-Pro | Qwen3 235B-A22B | |
|---|---|---|
| Provider | Xiaomi | Alibaba (Qwen) |
| Noometry Index | 43.0 | 43.5 |
| Released | 2026-03-18 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 131K |
| Max output | 131K | 16K |
| Input $ / M tokens | $0.43 | $0.70 |
| Output $ / M tokens | $0.87 | $2.80 |
| Results tracked | 23 | 49 |
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Category by category
Coding Too close to call
MiMo-V2-Pro: 43.8 (#83), Qwen3 235B-A22B: 44.3 (#75)
| Benchmark | MiMo-V2-Pro | Qwen3 235B-A22B |
|---|---|---|
| LMArena Coding | 1476 | 1445 |
| Aider Polyglot | — | 59.6% |
| LMArena WebDev | 1433 | — |
| SciCode | — | 42.4% |
| WeirdML | — | 41% |
| ALE-Bench | 785.17 | — |
Agentic & Tool Use Not comparable
MiMo-V2-Pro: —, Qwen3 235B-A22B: 33.9 (#51)
| Benchmark | MiMo-V2-Pro | Qwen3 235B-A22B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 52.1% |
| Vending-Bench 2 | — | -11.34 |
Reasoning MiMo-V2-Pro leads
MiMo-V2-Pro: 22.1 (#206), Qwen3 235B-A22B: 15.7 (#311)
| Benchmark | MiMo-V2-Pro | Qwen3 235B-A22B |
|---|---|---|
| LMArena Hard Prompts | 1457 | 1433 |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 31% |
| Kagi LLM Benchmark | — | 69.4% |
| NYT Connections (extended) | 25.8% | — |
| ARC-AGI-1 | — | 11% |
| CritPt | — | 0% |
| Chess Puzzles | — | 12% |
| Thematic Generalization | 45.9% | — |
| Mystery Game Puzzles | — | 9% |
| DTBench | — | 80.3% |
| LMCA | — | 29.3% |
| Epoch Capabilities Index | — | 143.85 |
| ForecastBench | — | 59.7 |
Math Qwen3 235B-A22B leads
MiMo-V2-Pro: 39.5 (#102), Qwen3 235B-A22B: 50.4 (#57)
| Benchmark | MiMo-V2-Pro | Qwen3 235B-A22B |
|---|---|---|
| LMArena Math | 1447 | 1432 |
| OTIS Mock AIME 2024-2025 | — | 86.7% |
| 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-Pro: 41.4 (#111), Qwen3 235B-A22B: 49.6 (#73)
| Benchmark | MiMo-V2-Pro | Qwen3 235B-A22B |
|---|---|---|
| LMArena Expert | 1478 | 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% |
Multilingual Too close to call
MiMo-V2-Pro: 52.7 (#81), Qwen3 235B-A22B: 52.3 (#89)
| Benchmark | MiMo-V2-Pro | Qwen3 235B-A22B |
|---|---|---|
| LMArena Non-English | 1416 | 1409 |
| LMArena Chinese | 1456 | 1481 |
| LMArena French | 1469 | 1445 |
| LMArena German | 1417 | 1433 |
| LMArena Japanese | 1366 | 1399 |
| LMArena Korean | 1400 | 1391 |
| LMArena Russian | 1427 | 1411 |
| LMArena Spanish | 1457 | 1430 |
Instruction Following MiMo-V2-Pro leads
MiMo-V2-Pro: 76.0 (#49), Qwen3 235B-A22B: 72.6 (#136)
| Benchmark | MiMo-V2-Pro | Qwen3 235B-A22B |
|---|---|---|
| LMArena Instruction Following | 1445 | 1408 |
| IFEval | — | 83.5% |
Long Context Qwen3 235B-A22B leads
MiMo-V2-Pro: 41.5 (#138), Qwen3 235B-A22B: 46.1 (#26)
| Benchmark | MiMo-V2-Pro | Qwen3 235B-A22B |
|---|---|---|
| LMArena Longer Query | 1455 | 1426 |
| Fiction.LiveBench | — | 75% |
| CL-bench | 15.7% | — |
| CL-bench Life | 6.9% | — |
Writing & Preference MiMo-V2-Pro leads
MiMo-V2-Pro: 62.8 (#70), Qwen3 235B-A22B: 59.6 (#108)
| Benchmark | MiMo-V2-Pro | Qwen3 235B-A22B |
|---|---|---|
| LMArena Text | 1436 | 1419 |
| LMArena Creative Writing | 1415 | 1384 |
| LMArena Multi-Turn | 1456 | 1432 |
| Short-Story Creative Writing | — | 83% |
| EQ-Bench Creative Writing | — | 1366 |
| WildBench | — | 86.6% |
Frequently asked questions
Is MiMo-V2-Pro better than Qwen3 235B-A22B?
MiMo-V2-Pro and Qwen3 235B-A22B score almost the same on the Noometry Index (43.0 vs 43.5), so choose on price, context window or the category you care about most.
Which is cheaper, MiMo-V2-Pro or Qwen3 235B-A22B?
MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; Qwen3 235B-A22B lists at $0.70 and $2.80.
Is MiMo-V2-Pro or Qwen3 235B-A22B better for coding?
They score almost the same on coding (43.8 vs 44.3); test both on your own repository before choosing.
Which has the bigger context window?
MiMo-V2-Pro does, with 1.05M tokens against 131K.
How many benchmarks do MiMo-V2-Pro and Qwen3 235B-A22B share?
17 benchmarks have published results for both models. MiMo-V2-Pro has 23 scored results on Noometry and Qwen3 235B-A22B has 49.