Mistral Small 24B Instruct 2501 — Benchmarks
Benchmark scores for Mistral Small 24B Instruct 2501 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 Small 24B Instruct 2501: 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 Small 24B Instruct 2501 reasoning benchmarks
Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.
47.3%
47.3%
median 55.7%open leader 93.2%
Overall best: Gemini 4 Argon (high) 96.4%
37th percentile · #63 of 100 open · #248 of 309 all
IndependentEpoch AI ·
Mistral Small 24B Instruct 2501 math benchmarks
Symbolic and quantitative problem-solving, from competition math to multi-step calculation.
6.7%
6.7%
median 54.4%open leader 99.4%
Overall best: Claude Fable 5 (high) 100.0%
23rd percentile · #68 of 88 open · #254 of 292 all
IndependentEpoch AI ·
44.8%
44.8%
median 41.6%open leader 96.6%
Overall best: GPT 5 (Aug 07, 2025, high) 98.1%
57th percentile · #18 of 39 open · #69 of 107 all
IndependentEpoch AI ·
Mistral Small 24B Instruct 2501 instruction following benchmarks
How precisely a model obeys explicit, verifiable instructions — format, length, and content constraints — and, more broadly, how much people prefer its responses head-to-head in blind human voting.
1274.4
1274.4
median 1321.4open leader 1488.2
Overall best: Gemini 4 Carbon (High) 1527.5
35th percentile · #122 of 188 open · #301 of 408 all
ArenaArena ·
Scores aggregated from public benchmark sources (Epoch AI: 3 boards, Arena: 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.