Mistral 7B Instruct v0.3 — Benchmarks
Benchmark scores for Mistral 7B Instruct v0.3 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 7B Instruct v0.3: 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 7B Instruct v0.3 reasoning benchmarks
Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.
15.2%
15.2%
median 54.0%open leader 93.1%
Overall best: Gemini 4 Argon (high) 96.4%
3rd percentile · #95 of 98 open · #296 of 300 all
IndependentEpoch AI ·
Mistral 7B Instruct v0.3 math benchmarks
Symbolic and quantitative problem-solving, from competition math to multi-step calculation.
0.3%
0.3%
median 52.8%open leader 98.6%
Overall best: Claude Fable 5 (high) 100.0%
2nd percentile · #85 of 86 open · #282 of 283 all
IndependentEpoch AI ·
3.6%
3.6%
median 41.6%open leader 96.6%
Overall best: GPT 5 (Aug 07, 2025, high) 98.1%
3rd percentile · #38 of 39 open · #106 of 107 all
IndependentEpoch AI ·
Mistral 7B Instruct v0.3 knowledge benchmarks
Breadth and depth of factual knowledge across many subjects, paired with the reasoning to apply it.
Scores aggregated from public benchmark sources (Epoch AI: 4 boards) — 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.