Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 2.5 Pro is clearly ahead on the aggregate, 67 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 2.5 Pro's sharpest advantage is in multimodal & grounded, where it averages 85.1 against 41.7. The single biggest benchmark swing on the page is MMMU-Pro, 86 to 39.
Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.03 input / $0.12 output per 1M tokens for LFM2-24B-A2B. That is roughly 41.7x on output cost alone. Gemini 2.5 Pro gives you the larger context window at 1M, compared with 32K for LFM2-24B-A2B.
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if you want the cheaper token bill.
Gemini 2.5 Pro
61.7
LFM2-24B-A2B
33.4
Gemini 2.5 Pro
41
LFM2-24B-A2B
18
Gemini 2.5 Pro
85.1
LFM2-24B-A2B
41.7
Gemini 2.5 Pro
80.7
LFM2-24B-A2B
46.6
Gemini 2.5 Pro
58.4
LFM2-24B-A2B
35.6
Gemini 2.5 Pro
83
LFM2-24B-A2B
68
Gemini 2.5 Pro
82.7
LFM2-24B-A2B
61.4
Gemini 2.5 Pro
83.5
LFM2-24B-A2B
50.4
Gemini 2.5 Pro is ahead overall, 67 to 38. The biggest single separator in this matchup is MMMU-Pro, where the scores are 86 and 39.
Gemini 2.5 Pro has the edge for knowledge tasks in this comparison, averaging 58.4 versus 35.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for coding in this comparison, averaging 41 versus 18. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for math in this comparison, averaging 83.5 versus 50.4. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for reasoning in this comparison, averaging 80.7 versus 46.6. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for agentic tasks in this comparison, averaging 61.7 versus 33.4. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 85.1 versus 41.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro 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.
Gemini 2.5 Pro has the edge for multilingual tasks in this comparison, averaging 82.7 versus 61.4. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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