Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Mistral Large 3 is clearly ahead on the aggregate, 61 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mistral Large 3's sharpest advantage is in multimodal & grounded, where it averages 75.5 against 41.7. The single biggest benchmark swing on the page is MMMU-Pro, 75 to 39.
Mistral Large 3 is also the more expensive model on tokens at $2.00 input / $6.00 output per 1M tokens, versus $0.03 input / $0.12 output per 1M tokens for LFM2-24B-A2B. That is roughly 50.0x on output cost alone. Mistral Large 3 gives you the larger context window at 128K, compared with 32K for LFM2-24B-A2B.
Pick Mistral Large 3 if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if you want the cheaper token bill.
Mistral Large 3
52.5
LFM2-24B-A2B
33.4
Mistral Large 3
41
LFM2-24B-A2B
18
Mistral Large 3
75.5
LFM2-24B-A2B
41.7
Mistral Large 3
70.6
LFM2-24B-A2B
46.6
Mistral Large 3
57.1
LFM2-24B-A2B
35.6
Mistral Large 3
83
LFM2-24B-A2B
68
Mistral Large 3
78.8
LFM2-24B-A2B
61.4
Mistral Large 3
77.3
LFM2-24B-A2B
50.4
Mistral Large 3 is ahead overall, 61 to 38. The biggest single separator in this matchup is MMMU-Pro, where the scores are 75 and 39.
Mistral Large 3 has the edge for knowledge tasks in this comparison, averaging 57.1 versus 35.6. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for coding in this comparison, averaging 41 versus 18. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for math in this comparison, averaging 77.3 versus 50.4. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for reasoning in this comparison, averaging 70.6 versus 46.6. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for agentic tasks in this comparison, averaging 52.5 versus 33.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for multimodal and grounded tasks in this comparison, averaging 75.5 versus 41.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for instruction following in this comparison, averaging 83 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for multilingual tasks in this comparison, averaging 78.8 versus 61.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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