Model comparison
MiMo-V2.5-Pro vs Qwen3-Next 80B-A3B Instruct
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 43.0 on the Noometry Index.
Last verified . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. MiMo-V2.5-Pro scores higher in 7 categories and Qwen3-Next 80B-A3B Instruct in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in long context, where MiMo-V2.5-Pro leads 45.4 to 37.0.
- MiMo-V2.5-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.50 / $2 for Qwen3-Next 80B-A3B Instruct.
- MiMo-V2.5-Pro accepts more context: 1.05M tokens versus 131K.
Side by side
| MiMo-V2.5-Pro | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | Xiaomi | Alibaba (Qwen) |
| Noometry Index | 45.2 | 43.0 |
| Released | 2026-04-22 | 2025-09 |
| Weights | Open | Open |
| Context window | 1.05M | 131K |
| Max output | 131K | 33K |
| Input $ / M tokens | $0.43 | $0.50 |
| Output $ / M tokens | $0.87 | $2 |
| Results tracked | 27 | 25 |
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Category by category
Coding MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 47.4 (#60), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | MiMo-V2.5-Pro | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Coding | 1503 | 1440 |
| LMArena WebDev | 1479 | — |
| SciCode | 50.2% | — |
| ALE-Bench | 899.8 | — |
Reasoning Qwen3-Next 80B-A3B Instruct leads
MiMo-V2.5-Pro: 26.8 (#130), Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | MiMo-V2.5-Pro | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1488 | 1428 |
| Kagi LLM Benchmark | — | 66.7% |
| NYT Connections (extended) | 34.4% | — |
| CritPt | 4% | — |
| DTBench | 84.5% | — |
| LMCA | 29.5% | — |
Math MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 40.0 (#96), Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | MiMo-V2.5-Pro | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Math | 1481 | 1440 |
| ProofBench | 22% | — |
| Omni-MATH | — | 46.7% |
Knowledge Too close to call
MiMo-V2.5-Pro: 42.2 (#98), Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | MiMo-V2.5-Pro | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Expert | 1503 | 1417 |
| MMLU-Pro | — | 78.6% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 63% |
Multilingual MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 55.1 (#34), Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | MiMo-V2.5-Pro | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | 1449 | 1407 |
| LMArena Chinese | 1507 | 1460 |
| LMArena French | 1488 | 1413 |
| LMArena German | 1458 | 1417 |
| LMArena Japanese | 1412 | 1395 |
| LMArena Korean | 1437 | 1364 |
| LMArena Russian | 1450 | 1404 |
| LMArena Spanish | 1471 | 1435 |
Instruction Following MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 77.5 (#21), Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | MiMo-V2.5-Pro | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Instruction Following | 1477 | 1389 |
| IFEval | — | 81% |
Long Context MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 45.4 (#37), Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | MiMo-V2.5-Pro | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Longer Query | 1483 | 1403 |
| Fiction.LiveBench | — | 55.6% |
Writing & Preference MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 65.3 (#49), Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | MiMo-V2.5-Pro | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | 1465 | 1417 |
| LMArena Creative Writing | 1440 | 1334 |
| LMArena Multi-Turn | 1477 | 1416 |
| EQ-Bench Creative Writing | 1493 | — |
| WildBench | — | 80.7% |
| EQ-Bench 4 | 1208 | — |
Frequently asked questions
Is MiMo-V2.5-Pro better than Qwen3-Next 80B-A3B Instruct?
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 43.0 on the Noometry Index.
Which is cheaper, MiMo-V2.5-Pro or Qwen3-Next 80B-A3B Instruct?
MiMo-V2.5-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; Qwen3-Next 80B-A3B Instruct lists at $0.50 and $2.
Is MiMo-V2.5-Pro or Qwen3-Next 80B-A3B Instruct better for coding?
MiMo-V2.5-Pro scores higher on coding benchmarks: 47.4 versus 42.5 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.5-Pro does, with 1.05M tokens against 131K.
How many benchmarks do MiMo-V2.5-Pro and Qwen3-Next 80B-A3B Instruct share?
17 benchmarks have published results for both models. MiMo-V2.5-Pro has 27 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.