Model comparison
MiMo-V2.5-Pro vs Mistral Small
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 33.4 on the Noometry Index. Mistral Small costs 2.1× less per token, which makes it the better buy when MiMo-V2.5-Pro's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Mistral AISummary
- They share 22 benchmarks with published results for both. MiMo-V2.5-Pro scores higher in 8 categories and Mistral Small in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where MiMo-V2.5-Pro leads 40.0 to 16.4.
- The biggest single-benchmark swing is SciCode: 50.2% for MiMo-V2.5-Pro and 26.5% for Mistral Small.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2.5-Pro.
- MiMo-V2.5-Pro accepts more context: 1.05M tokens versus 262K.
Side by side
| MiMo-V2.5-Pro | Mistral Small | |
|---|---|---|
| Provider | Xiaomi | Mistral AI |
| Noometry Index | 45.2 | 33.4 |
| Released | 2026-04-22 | 2024-02-26 |
| Weights | Open | Open |
| Context window | 1.05M | 262K |
| Max output | 131K | 256K |
| Input $ / M tokens | $0.43 | $0.15 |
| Output $ / M tokens | $0.87 | $0.60 |
| Results tracked | 27 | 39 |
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Category by category
Coding MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 47.4 (#60), Mistral Small: 34.0 (#247)
| Benchmark | MiMo-V2.5-Pro | Mistral Small |
|---|---|---|
| SciCode | 50.2% | 26.5% |
| LMArena Coding | 1503 | 1362 |
| ALE-Bench | 899.8 | 497.62 |
| LMArena WebDev | 1479 | — |
| BigCodeBench Instruct | — | 36.1% |
| LiveBench Coding | — | 36.2% |
| BigCodeBench Complete | — | 46.6% |
Agentic & Tool Use Not comparable
MiMo-V2.5-Pro: —, Mistral Small: 28.1 (#93)
| Benchmark | MiMo-V2.5-Pro | Mistral Small |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.1% |
Reasoning MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 26.8 (#130), Mistral Small: 19.8 (#250)
| Benchmark | MiMo-V2.5-Pro | Mistral Small |
|---|---|---|
| CritPt | 4% | 0% |
| LMArena Hard Prompts | 1488 | 1335 |
| DTBench | 84.5% | 70.9% |
| LMCA | 29.5% | 20.6% |
| Kagi LLM Benchmark | — | 37.8% |
| NYT Connections (extended) | 34.4% | — |
| LiveBench Reasoning | — | 44.8% |
| LiveBench Data Analysis | — | 53.7% |
| LiveBench | — | 44% |
Math MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 40.0 (#96), Mistral Small: 16.4 (#293)
| Benchmark | MiMo-V2.5-Pro | Mistral Small |
|---|---|---|
| LMArena Math | 1481 | 1341 |
| OTIS Mock AIME 2024-2025 | — | 5.8% |
| ProofBench | 22% | — |
| LiveBench Math | — | 39.9% |
| MATH Level 5 | — | 46.8% |
Knowledge MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 42.2 (#98), Mistral Small: 31.0 (#222)
| Benchmark | MiMo-V2.5-Pro | Mistral Small |
|---|---|---|
| LMArena Expert | 1503 | 1291 |
| GPQA Diamond | — | 47.5% |
| Vectara Hallucination Rate | — | 5.1% |
| MMLU | — | 68.7% |
Multimodal Not comparable
MiMo-V2.5-Pro: —, Mistral Small: 33.5 (#96)
| Benchmark | MiMo-V2.5-Pro | Mistral Small |
|---|---|---|
| LMArena Vision | — | 1142 |
Multilingual MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 55.1 (#34), Mistral Small: 45.5 (#169)
| Benchmark | MiMo-V2.5-Pro | Mistral Small |
|---|---|---|
| LMArena Non-English | 1449 | 1315 |
| LMArena Chinese | 1507 | 1340 |
| LMArena French | 1488 | 1337 |
| LMArena German | 1458 | 1340 |
| LMArena Japanese | 1412 | 1275 |
| LMArena Korean | 1437 | 1259 |
| LMArena Russian | 1450 | 1324 |
| LMArena Spanish | 1471 | 1346 |
Instruction Following MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 77.5 (#21), Mistral Small: 66.4 (#209)
| Benchmark | MiMo-V2.5-Pro | Mistral Small |
|---|---|---|
| LMArena Instruction Following | 1477 | 1310 |
| LiveBench Instruction Following | — | 63.7% |
Long Context MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 45.4 (#37), Mistral Small: 40.4 (#156)
| Benchmark | MiMo-V2.5-Pro | Mistral Small |
|---|---|---|
| LMArena Longer Query | 1483 | 1327 |
Writing & Preference MiMo-V2.5-Pro leads
MiMo-V2.5-Pro: 65.3 (#49), Mistral Small: 52.5 (#171)
| Benchmark | MiMo-V2.5-Pro | Mistral Small |
|---|---|---|
| LMArena Text | 1465 | 1338 |
| LMArena Creative Writing | 1440 | 1305 |
| LMArena Multi-Turn | 1477 | 1344 |
| EQ-Bench Creative Writing | 1493 | — |
| EQ-Bench 4 | 1208 | — |
| LiveBench Language | — | 30.5% |
Frequently asked questions
Is MiMo-V2.5-Pro better than Mistral Small?
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 33.4 on the Noometry Index. Mistral Small costs 2.1× less per token, which makes it the better buy when MiMo-V2.5-Pro's lead doesn't matter for your workload.
Which is cheaper, MiMo-V2.5-Pro or Mistral Small?
Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; MiMo-V2.5-Pro lists at $0.43 and $0.87.
Is MiMo-V2.5-Pro or Mistral Small better for coding?
MiMo-V2.5-Pro scores higher on coding benchmarks: 47.4 versus 34.0 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.5-Pro does, with 1.05M tokens against 262K.
How many benchmarks do MiMo-V2.5-Pro and Mistral Small share?
22 benchmarks have published results for both models. MiMo-V2.5-Pro has 27 scored results on Noometry and Mistral Small has 39.