Mistral Nemo Base 2407 — Benchmarks
Benchmark scores for Mistral Nemo Base 2407 aggregated from public leaderboards (4 boards), with how it ranks among open models and how it compares with its nearest neighbours. See hardware requirements for what you need to run it.
No llmrun Composite Score for Mistral Nemo Base 2407: the score is only published for a model measured on at least 4 of the boards in the score panel, spanning at least 2 benchmark categories and including a reasoning or coding board — or on 3 boards that narrow its score to a 90% range of at most 15.6 points. Either way the results must come from at least two different benchmarks. Its individual scores below stand on their own — see how the llmrun Composite Score gets calculated.
Mistral Nemo Base 2407 reasoning benchmarks
Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.
Mistral Nemo Base 2407 math benchmarks
Symbolic and quantitative problem-solving, from competition math to multi-step calculation.
Mistral Nemo Base 2407 knowledge benchmarks
Breadth and depth of factual knowledge across many subjects, paired with the reasoning to apply it.
39.8%
39.8%
median 52.0%open leader 88.0%
Overall best: Gemini-3.1-Pro 91.2%
30th percentile · #102 of 146 open · #198 of 257 all
Independent
Scores aggregated from public benchmark sources (Epoch AI: 3 boards, TIGER-Lab: 1 board) — each linked from the benchmark pages. llmrun does not run these benchmarks. Percentiles and ranks are among open models in the llmrun catalogue; the median and leader marks refer to the same field.