Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4o is clearly ahead on the aggregate, 56 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4o's sharpest advantage is in multimodal & grounded, where it averages 72.2 against 41.7. The single biggest benchmark swing on the page is MMMU-Pro, 74 to 39.
GPT-4o is also the more expensive model on tokens at $2.50 input / $10.00 output per 1M tokens, versus $0.03 input / $0.12 output per 1M tokens for LFM2-24B-A2B. That is roughly 83.3x on output cost alone. GPT-4o gives you the larger context window at 128K, compared with 32K for LFM2-24B-A2B.
Pick GPT-4o if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if you want the cheaper token bill.
GPT-4o
51.2
LFM2-24B-A2B
33.4
GPT-4o
32.2
LFM2-24B-A2B
18
GPT-4o
72.2
LFM2-24B-A2B
41.7
GPT-4o
64.6
LFM2-24B-A2B
46.6
GPT-4o
47.4
LFM2-24B-A2B
35.6
GPT-4o
82
LFM2-24B-A2B
68
GPT-4o
75.5
LFM2-24B-A2B
61.4
GPT-4o
71.8
LFM2-24B-A2B
50.4
GPT-4o is ahead overall, 56 to 38. The biggest single separator in this matchup is MMMU-Pro, where the scores are 74 and 39.
GPT-4o has the edge for knowledge tasks in this comparison, averaging 47.4 versus 35.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-4o has the edge for coding in this comparison, averaging 32.2 versus 18. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GPT-4o has the edge for math in this comparison, averaging 71.8 versus 50.4. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
GPT-4o has the edge for reasoning in this comparison, averaging 64.6 versus 46.6. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-4o has the edge for agentic tasks in this comparison, averaging 51.2 versus 33.4. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
GPT-4o has the edge for multimodal and grounded tasks in this comparison, averaging 72.2 versus 41.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-4o has the edge for instruction following in this comparison, averaging 82 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-4o has the edge for multilingual tasks in this comparison, averaging 75.5 versus 61.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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