Model comparison
Gemini 3.1 Pro Preview vs Mistral Nemo
Gemini 3.1 Pro Preview is the stronger model overall, scoring 56.7 to 26.4 on the Noometry Index. Mistral Nemo costs 30× 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 . 5 shared benchmarks.
Summary
- They share 5 benchmarks with published results for both. Gemini 3.1 Pro Preview scores higher in 5 categories and Mistral Nemo in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Gemini 3.1 Pro Preview leads 71.8 to 12.3.
- The biggest single-benchmark swing is GPQA Diamond: 94.4% for Gemini 3.1 Pro Preview and 29.9% for Mistral Nemo.
- Mistral Nemo is cheaper at $0.15 / $0.15 per million input/output tokens, against $2 / $12 for Gemini 3.1 Pro Preview.
- Gemini 3.1 Pro Preview accepts more context: 1.05M tokens versus 128K.
- Mistral Nemo has downloadable open weights; the other is API-only.
Side by side
| Gemini 3.1 Pro Preview | Mistral Nemo | |
|---|---|---|
| Provider | Mistral AI | |
| Noometry Index | 56.7 | 26.4 |
| Released | 2026-02-19 | 2024-07-01 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 66K | 128K |
| Input $ / M tokens | $2 | $0.15 |
| Output $ / M tokens | $12 | $0.15 |
| Results tracked | 71 | 10 |
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Category by category
Coding Not comparable
Gemini 3.1 Pro Preview: 42.5 (#99), Mistral Nemo: —
| Benchmark | Gemini 3.1 Pro Preview | Mistral Nemo |
|---|---|---|
| SWE-bench Verified | 75.6% | — |
| DeepSWE | 11.7% | — |
| LMArena WebDev | 1447 | — |
| SciCode | 58.9% | — |
| GSO | 22.6% | — |
| WeirdML | 72.1% | — |
| LMArena Coding | 1484 | — |
| MirrorCode | 8.9% | — |
| ALE-Bench | 1,161 | — |
| AlgoTune | 2.02 | — |
Agentic & Tool Use Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 37.7 (#34), Mistral Nemo: 23.5 (#125)
| Benchmark | Gemini 3.1 Pro Preview | Mistral Nemo |
|---|---|---|
| BALROG | 57% | 17.6% |
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 35.3% | — |
| Berkeley Function Calling Leaderboard | — | 27.6% |
| τ²-bench Banking | 26% | — |
| DeepResearch Bench | 47.8% | — |
| PostTrainBench | 22% | — |
| 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), Mistral Nemo: 20.7 (#232)
| Benchmark | Gemini 3.1 Pro Preview | Mistral Nemo |
|---|---|---|
| DTBench | 97.1% | 48.6% |
| Epoch Capabilities Index | 154.77 | 118.68 |
| ARC-AGI-2 | 77.1% | — |
| SimpleBench | 79.6% | — |
| NYT Connections (extended) | 97.4% | — |
| ARC-AGI-1 | 98% | — |
| CritPt | 17.7% | — |
| Chess Puzzles | 55% | — |
| EnigmaEval | 36.8% | — |
| Thematic Generalization | 79.4% | — |
| EBR-Bench | 14.3% | — |
| LMArena Hard Prompts | 1485 | — |
| Mystery Game Puzzles | 34% | — |
| LMCA | 53.8% | — |
| ForecastBench | 59 | — |
| PIQA | — | 83.5% |
Math Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 62.1 (#34), Mistral Nemo: 25.5 (#268)
| Benchmark | Gemini 3.1 Pro Preview | Mistral Nemo |
|---|---|---|
| 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% | — |
| LMArena Math | 1485 | — |
| MATH Level 5 | — | 10.8% |
| FrontierMath (Feb 2025 set) | 36.9% | — |
| FrontierMath Tier 4 (v1) | 16.7% | — |
| GSM8K | — | 84.2% |
Knowledge Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 71.8 (#3), Mistral Nemo: 12.3 (#298)
| Benchmark | Gemini 3.1 Pro Preview | Mistral Nemo |
|---|---|---|
| GPQA Diamond | 94.4% | 29.9% |
| Humanity's Last Exam | 46.4% | — |
| SimpleQA Verified | 73.5% | — |
| Vectara Hallucination Rate | 10.4% | — |
| LMArena Expert | 1485 | — |
| BoolQ | — | 82.5% |
Multimodal Not comparable
Gemini 3.1 Pro Preview: 37.9 (#69), Mistral Nemo: —
| Benchmark | Gemini 3.1 Pro Preview | Mistral Nemo |
|---|---|---|
| LMArena Vision | 1296 | — |
| Blueprint-Bench 2 | 26.5% | — |
| Furniture Assembly | 26.7% | — |
| LMArena Document | 1444 | — |
Multilingual Not comparable
Gemini 3.1 Pro Preview: 57.0 (#12), Mistral Nemo: —
| Benchmark | Gemini 3.1 Pro Preview | Mistral Nemo |
|---|---|---|
| LMArena Non-English | 1477 | — |
| LMArena Chinese | 1529 | — |
| LMArena French | 1487 | — |
| LMArena German | 1491 | — |
| LMArena Japanese | 1493 | — |
| LMArena Korean | 1455 | — |
| LMArena Russian | 1498 | — |
| LMArena Spanish | 1479 | — |
Instruction Following Not comparable
Gemini 3.1 Pro Preview: 77.0 (#32), Mistral Nemo: —
| Benchmark | Gemini 3.1 Pro Preview | Mistral Nemo |
|---|---|---|
| LMArena Instruction Following | 1466 | — |
Long Context Not comparable
Gemini 3.1 Pro Preview: 47.4 (#18), Mistral Nemo: —
| Benchmark | Gemini 3.1 Pro Preview | Mistral Nemo |
|---|---|---|
| CL-bench | 20.8% | — |
| CL-bench Life | 16.9% | — |
| LMArena Longer Query | 1483 | — |
Writing & Preference Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 66.1 (#37), Mistral Nemo: 28.5 (#296)
| Benchmark | Gemini 3.1 Pro Preview | Mistral Nemo |
|---|---|---|
| EQ-Bench Creative Writing | 1491 | 881 |
| LMArena Text | 1481 | — |
| LMArena Creative Writing | 1482 | — |
| EQ-Bench 4 | 1142 | — |
| LMArena Multi-Turn | 1488 | — |
Frequently asked questions
Is Gemini 3.1 Pro Preview better than Mistral Nemo?
Gemini 3.1 Pro Preview is the stronger model overall, scoring 56.7 to 26.4 on the Noometry Index. Mistral Nemo costs 30× 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 Mistral Nemo?
Mistral Nemo is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; Gemini 3.1 Pro Preview lists at $2 and $12.
Which has the bigger context window?
Gemini 3.1 Pro Preview does, with 1.05M tokens against 128K.
How many benchmarks do Gemini 3.1 Pro Preview and Mistral Nemo share?
5 benchmarks have published results for both models. Gemini 3.1 Pro Preview has 71 scored results on Noometry and Mistral Nemo has 10.