Model comparison
MiMo-V2-Pro vs Pixtral Large
MiMo-V2-Pro is the stronger model overall, scoring 42.4 to 31.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
Mistral AISummary
- The widest gap is in writing & preference, where MiMo-V2-Pro leads 62.9 to 32.9.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $2 / $6 for Pixtral Large.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 128K.
- Pixtral Large has downloadable open weights; the other is API-only.
Side by side
| MiMo-V2-Pro | Pixtral Large | |
|---|---|---|
| Provider | Xiaomi | Mistral AI |
| Noometry Index | 42.4 | 31.7 |
| Released | 2026-03-18 | 2024-11-01 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 131K | 128K |
| Input $ / M tokens | $0.43 | $2 |
| Output $ / M tokens | $0.87 | $6 |
| Results tracked | 23 | 3 |
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Category by category
Coding Not comparable
MiMo-V2-Pro: 43.4 (#76), Pixtral Large: —
| Benchmark | MiMo-V2-Pro | Pixtral Large |
|---|---|---|
| LMArena WebDev | 1433 | — |
| LMArena Coding | 1476 | — |
| ALE-Bench | 785.17 | — |
Reasoning Too close to call
MiMo-V2-Pro: 21.3 (#200), Pixtral Large: 20.9 (#208)
| Benchmark | MiMo-V2-Pro | Pixtral Large |
|---|---|---|
| NYT Connections (extended) | 25.8% | — |
| EnigmaEval | — | 0.8% |
| Thematic Generalization | 45.9% | — |
| LMArena Hard Prompts | 1457 | — |
Math Not comparable
MiMo-V2-Pro: 36.7 (#104), Pixtral Large: —
| Benchmark | MiMo-V2-Pro | Pixtral Large |
|---|---|---|
| LMArena Math | 1447 | — |
Knowledge Not comparable
MiMo-V2-Pro: 40.8 (#106), Pixtral Large: —
| Benchmark | MiMo-V2-Pro | Pixtral Large |
|---|---|---|
| LMArena Expert | 1479 | — |
Multimodal Not comparable
MiMo-V2-Pro: —, Pixtral Large: 30.0 (#105)
| Benchmark | MiMo-V2-Pro | Pixtral Large |
|---|---|---|
| LMArena Vision | — | 1089 |
Multilingual Not comparable
MiMo-V2-Pro: 52.9 (#77), Pixtral Large: —
| Benchmark | MiMo-V2-Pro | Pixtral Large |
|---|---|---|
| LMArena Non-English | 1416 | — |
| LMArena Chinese | 1455 | — |
| LMArena French | 1470 | — |
| LMArena German | 1417 | — |
| LMArena Japanese | 1366 | — |
| LMArena Korean | 1401 | — |
| LMArena Russian | 1427 | — |
| LMArena Spanish | 1458 | — |
Instruction Following Not comparable
MiMo-V2-Pro: 76.2 (#46), Pixtral Large: —
| Benchmark | MiMo-V2-Pro | Pixtral Large |
|---|---|---|
| LMArena Instruction Following | 1444 | — |
Long Context Not comparable
MiMo-V2-Pro: 41.5 (#133), Pixtral Large: —
| Benchmark | MiMo-V2-Pro | Pixtral Large |
|---|---|---|
| CL-bench | 15.7% | — |
| CL-bench Life | 6.9% | — |
| LMArena Longer Query | 1455 | — |
Writing & Preference MiMo-V2-Pro leads
MiMo-V2-Pro: 62.9 (#67), Pixtral Large: 32.9 (#273)
| Benchmark | MiMo-V2-Pro | Pixtral Large |
|---|---|---|
| LMArena Text | 1436 | — |
| LMArena Creative Writing | 1415 | — |
| EQ-Bench Creative Writing | — | 988 |
| LMArena Multi-Turn | 1456 | — |
Frequently asked questions
Is MiMo-V2-Pro better than Pixtral Large?
MiMo-V2-Pro is the stronger model overall, scoring 42.4 to 31.7 on the Noometry Index.
Which is cheaper, MiMo-V2-Pro or Pixtral Large?
MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; Pixtral Large lists at $2 and $6.
Which has the bigger context window?
MiMo-V2-Pro does, with 1.05M tokens against 128K.
How many benchmarks do MiMo-V2-Pro and Pixtral Large share?
0 benchmarks have published results for both models. MiMo-V2-Pro has 23 scored results on Noometry and Pixtral Large has 3.