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 33. 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 32.4. The single biggest benchmark swing on the page is HumanEval, 68 to 17.
Mistral Large 3 is also the more expensive model on tokens at $2.00 input / $6.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2.5-1.2B-Thinking. That is roughly Infinityx on output cost alone. LFM2.5-1.2B-Thinking is the reasoning model in the pair, while Mistral Large 3 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Mistral Large 3 gives you the larger context window at 128K, compared with 32K for LFM2.5-1.2B-Thinking.
Pick Mistral Large 3 if you want the stronger benchmark profile. LFM2.5-1.2B-Thinking only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Mistral Large 3
52.5
LFM2.5-1.2B-Thinking
34.1
Mistral Large 3
41
LFM2.5-1.2B-Thinking
8.2
Mistral Large 3
75.5
LFM2.5-1.2B-Thinking
32.4
Mistral Large 3
70.6
LFM2.5-1.2B-Thinking
38.4
Mistral Large 3
57.1
LFM2.5-1.2B-Thinking
27
Mistral Large 3
83
LFM2.5-1.2B-Thinking
72
Mistral Large 3
78.8
LFM2.5-1.2B-Thinking
60.7
Mistral Large 3
77.3
LFM2.5-1.2B-Thinking
42.3
Mistral Large 3 is ahead overall, 61 to 33. The biggest single separator in this matchup is HumanEval, where the scores are 68 and 17.
Mistral Large 3 has the edge for knowledge tasks in this comparison, averaging 57.1 versus 27. 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 8.2. Inside this category, HumanEval 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 42.3. 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 38.4. 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 34.1. Inside this category, BrowseComp 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 32.4. 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 72. 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 60.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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