Mistral AI
Mistral NeMo benchmark results
7 results on 5 benchmarks from 4 sources.
Also listed as: open-mistral-nemo-2407 · Open-Mistral-Nemo-2407 (FC) · Open-Mistral-Nemo-2407 (Prompt) · Mistral-Nemo-Instruct-2407 · Mistral-Nemo-Base-2407 · mistralai/Mistral-Nemo-Instruct-2407 · mistralai/Mistral-Nemo-Base-2407
All benchmark results
| Benchmarks | Score | Rank | Setting | Source type | Date |
|---|---|---|---|---|---|
| Open LLM Leaderboard v2 | 24.7% | 1676 | Average of 6 normalised benchmarks; bfloat16; 12.248B params“mistralai/Mistral-Nemo-Instruct-2407” | Official leaderboard | Mar 13, 2025 |
| Open LLM Leaderboard v2 | 15.2% | 3276 | Average of 6 normalised benchmarks; bfloat16; 11.58B params“mistralai/Mistral-Nemo-Base-2407” | Official leaderboard | Mar 13, 2025 |
| GPQA Diamond | 29.9% | 262 | Epoch AI run, accuracy | Independent run | Jan 27, 2025 |
| MMLU-Pro | 44.8% | 177 | Overall accuracy; data source: TIGER-Lab; 12B“Mistral-Nemo-Instruct-2407” | Official leaderboard | Mar 11, 2026 |
| MATH Level 5 | 10.8% | 98 | Epoch AI run, accuracy | Independent run | Jan 27, 2025 |
| BFCL v4 (function calling) | 27.6% | 78 | Overall accuracy; native function calling (FC)“Open-Mistral-Nemo-2407 (FC)” | Official leaderboard | Oct 17, 2026 |
| BFCL v4 (function calling) | 19.3% | 102 | Overall accuracy; prompt-based“Open-Mistral-Nemo-2407 (Prompt)” | Official leaderboard | Oct 17, 2026 |
FAQ
Where do these Mistral NeMo scores come from?
From Berkeley Function Calling Leaderboard (BFCL), Epoch AI Benchmarking Hub, MMLU-Pro leaderboard (TIGER-Lab), and Hugging Face Open LLM Leaderboard v2 (archived). Each row links to the original leaderboard, dataset or report, and vendor-reported numbers are labelled.