Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Claude Haiku 4.5 is clearly ahead on the aggregate, 62 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Haiku 4.5's sharpest advantage is in multimodal & grounded, where it averages 78.4 against 41.7. The single biggest benchmark swing on the page is MMMU-Pro, 82 to 39.
Claude Haiku 4.5 is also the more expensive model on tokens at $0.80 input / $4.00 output per 1M tokens, versus $0.03 input / $0.12 output per 1M tokens for LFM2-24B-A2B. That is roughly 33.3x on output cost alone. Claude Haiku 4.5 gives you the larger context window at 200K, compared with 32K for LFM2-24B-A2B.
Pick Claude Haiku 4.5 if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if you want the cheaper token bill.
Claude Haiku 4.5
56.7
LFM2-24B-A2B
33.4
Claude Haiku 4.5
41.7
LFM2-24B-A2B
18
Claude Haiku 4.5
78.4
LFM2-24B-A2B
41.7
Claude Haiku 4.5
68.9
LFM2-24B-A2B
46.6
Claude Haiku 4.5
53.6
LFM2-24B-A2B
35.6
Claude Haiku 4.5
86
LFM2-24B-A2B
68
Claude Haiku 4.5
80.1
LFM2-24B-A2B
61.4
Claude Haiku 4.5
73.3
LFM2-24B-A2B
50.4
Claude Haiku 4.5 is ahead overall, 62 to 38. The biggest single separator in this matchup is MMMU-Pro, where the scores are 82 and 39.
Claude Haiku 4.5 has the edge for knowledge tasks in this comparison, averaging 53.6 versus 35.6. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for coding in this comparison, averaging 41.7 versus 18. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for math in this comparison, averaging 73.3 versus 50.4. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for reasoning in this comparison, averaging 68.9 versus 46.6. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for agentic tasks in this comparison, averaging 56.7 versus 33.4. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for multimodal and grounded tasks in this comparison, averaging 78.4 versus 41.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for instruction following in this comparison, averaging 86 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for multilingual tasks in this comparison, averaging 80.1 versus 61.4. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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