Model comparison
Gemini 3.1 Pro Preview vs MiMo-V2-Pro
Gemini 3.1 Pro Preview is the stronger model overall, scoring 56.7 to 43.0 on the Noometry Index. MiMo-V2-Pro costs 8.3× less per token, which makes it the better buy when Gemini 3.1 Pro Preview's lead doesn't matter for your workload.
Last verified . 23 shared benchmarks.
GoogleSummary
- They share 23 benchmarks with published results for both. Gemini 3.1 Pro Preview scores higher in 7 categories and MiMo-V2-Pro in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.1 Pro Preview leads 71.7 to 22.1.
- The biggest single-benchmark swing is NYT Connections (extended): 97.4% for Gemini 3.1 Pro Preview and 25.8% for MiMo-V2-Pro.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $2 / $12 for Gemini 3.1 Pro Preview.
Side by side
| Gemini 3.1 Pro Preview | MiMo-V2-Pro | |
|---|---|---|
| Provider | Xiaomi | |
| Noometry Index | 56.7 | 43.0 |
| Released | 2026-02-19 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 131K |
| Input $ / M tokens | $2 | $0.43 |
| Output $ / M tokens | $12 | $0.87 |
| Results tracked | 71 | 23 |
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Category by category
Coding MiMo-V2-Pro leads
Gemini 3.1 Pro Preview: 42.5 (#99), MiMo-V2-Pro: 43.8 (#83)
| Benchmark | Gemini 3.1 Pro Preview | MiMo-V2-Pro |
|---|---|---|
| LMArena WebDev | 1447 | 1433 |
| LMArena Coding | 1484 | 1476 |
| ALE-Bench | 1,161 | 785.17 |
| SWE-bench Verified | 75.6% | — |
| DeepSWE | 11.7% | — |
| SciCode | 58.9% | — |
| GSO | 22.6% | — |
| WeirdML | 72.1% | — |
| MirrorCode | 8.9% | — |
| AlgoTune | 2.02 | — |
Agentic & Tool Use Not comparable
Gemini 3.1 Pro Preview: 37.7 (#34), MiMo-V2-Pro: —
| Benchmark | Gemini 3.1 Pro Preview | MiMo-V2-Pro |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 35.3% | — |
| τ²-bench Banking | 26% | — |
| DeepResearch Bench | 47.8% | — |
| PostTrainBench | 22% | — |
| BALROG | 57% | — |
| ExploitBench | 26.1% | — |
| GBAEval | 0.8% | — |
| GDP.pdf | 17% | — |
| LMArena Search | 1211 | — |
| METR Time Horizons | 77% | — |
| Vending-Bench 2 | 3,774 | — |
Reasoning Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 71.7 (#12), MiMo-V2-Pro: 22.1 (#206)
| Benchmark | Gemini 3.1 Pro Preview | MiMo-V2-Pro |
|---|---|---|
| NYT Connections (extended) | 97.4% | 25.8% |
| Thematic Generalization | 79.4% | 45.9% |
| LMArena Hard Prompts | 1485 | 1457 |
| ARC-AGI-2 | 77.1% | — |
| SimpleBench | 79.6% | — |
| ARC-AGI-1 | 98% | — |
| CritPt | 17.7% | — |
| Chess Puzzles | 55% | — |
| EnigmaEval | 36.8% | — |
| EBR-Bench | 14.3% | — |
| Mystery Game Puzzles | 34% | — |
| DTBench | 97.1% | — |
| LMCA | 53.8% | — |
| Epoch Capabilities Index | 154.77 | — |
| ForecastBench | 59 | — |
Math Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 62.1 (#34), MiMo-V2-Pro: 39.5 (#102)
| Benchmark | Gemini 3.1 Pro Preview | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1485 | 1447 |
| FrontierMath (Tiers 1-3) | 59.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 86.5% | — |
| OTIS Mock AIME 2024-2025 | 95.6% | — |
| ProofBench | 26% | — |
| FrontierMath (Feb 2025 set) | 36.9% | — |
| FrontierMath Tier 4 (v1) | 16.7% | — |
Knowledge Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 71.8 (#3), MiMo-V2-Pro: 41.4 (#111)
| Benchmark | Gemini 3.1 Pro Preview | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1485 | 1478 |
| GPQA Diamond | 94.4% | — |
| Humanity's Last Exam | 46.4% | — |
| SimpleQA Verified | 73.5% | — |
| Vectara Hallucination Rate | 10.4% | — |
Multimodal Not comparable
Gemini 3.1 Pro Preview: 37.9 (#69), MiMo-V2-Pro: —
| Benchmark | Gemini 3.1 Pro Preview | MiMo-V2-Pro |
|---|---|---|
| LMArena Vision | 1296 | — |
| Blueprint-Bench 2 | 26.5% | — |
| Furniture Assembly | 26.7% | — |
| LMArena Document | 1444 | — |
Multilingual Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 57.0 (#12), MiMo-V2-Pro: 52.7 (#81)
| Benchmark | Gemini 3.1 Pro Preview | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1477 | 1416 |
| LMArena Chinese | 1529 | 1456 |
| LMArena French | 1487 | 1469 |
| LMArena German | 1491 | 1417 |
| LMArena Japanese | 1493 | 1366 |
| LMArena Korean | 1455 | 1400 |
| LMArena Russian | 1498 | 1427 |
| LMArena Spanish | 1479 | 1457 |
Instruction Following Too close to call
Gemini 3.1 Pro Preview: 77.0 (#32), MiMo-V2-Pro: 76.0 (#49)
| Benchmark | Gemini 3.1 Pro Preview | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1466 | 1445 |
Long Context Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 47.4 (#18), MiMo-V2-Pro: 41.5 (#138)
| Benchmark | Gemini 3.1 Pro Preview | MiMo-V2-Pro |
|---|---|---|
| CL-bench | 20.8% | 15.7% |
| CL-bench Life | 16.9% | 6.9% |
| LMArena Longer Query | 1483 | 1455 |
Writing & Preference Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 66.1 (#37), MiMo-V2-Pro: 62.8 (#70)
| Benchmark | Gemini 3.1 Pro Preview | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1481 | 1436 |
| LMArena Creative Writing | 1482 | 1415 |
| LMArena Multi-Turn | 1488 | 1456 |
| EQ-Bench Creative Writing | 1491 | — |
| EQ-Bench 4 | 1142 | — |
Frequently asked questions
Is Gemini 3.1 Pro Preview better than MiMo-V2-Pro?
Gemini 3.1 Pro Preview is the stronger model overall, scoring 56.7 to 43.0 on the Noometry Index. MiMo-V2-Pro costs 8.3× less per token, which makes it the better buy when Gemini 3.1 Pro Preview's lead doesn't matter for your workload.
Which is cheaper, Gemini 3.1 Pro Preview or MiMo-V2-Pro?
MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; Gemini 3.1 Pro Preview lists at $2 and $12.
Is Gemini 3.1 Pro Preview or MiMo-V2-Pro better for coding?
MiMo-V2-Pro scores higher on coding benchmarks: 43.8 versus 42.5 in the Noometry coding category.
Which has the bigger context window?
Both accept 1.05M tokens.
How many benchmarks do Gemini 3.1 Pro Preview and MiMo-V2-Pro share?
23 benchmarks have published results for both models. Gemini 3.1 Pro Preview has 71 scored results on Noometry and MiMo-V2-Pro has 23.