Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Step 3.5 Flash is clearly ahead on the aggregate, 66 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Step 3.5 Flash's sharpest advantage is in mathematics, where it averages 84.5 against 50.4. The single biggest benchmark swing on the page is MuSR, 82 to 42.
Step 3.5 Flash is also the more expensive model on tokens at $0.10 input / $0.30 output per 1M tokens, versus $0.03 input / $0.12 output per 1M tokens for LFM2-24B-A2B. That is roughly 2.5x on output cost alone. Step 3.5 Flash gives you the larger context window at 256K, compared with 32K for LFM2-24B-A2B.
Pick Step 3.5 Flash if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if you want the cheaper token bill.
Step 3.5 Flash
60.2
LFM2-24B-A2B
33.4
Step 3.5 Flash
47.1
LFM2-24B-A2B
18
Step 3.5 Flash
66.7
LFM2-24B-A2B
41.7
Step 3.5 Flash
78.3
LFM2-24B-A2B
46.6
Step 3.5 Flash
60.8
LFM2-24B-A2B
35.6
Step 3.5 Flash
87
LFM2-24B-A2B
68
Step 3.5 Flash
82.8
LFM2-24B-A2B
61.4
Step 3.5 Flash
84.5
LFM2-24B-A2B
50.4
Step 3.5 Flash is ahead overall, 66 to 38. The biggest single separator in this matchup is MuSR, where the scores are 82 and 42.
Step 3.5 Flash has the edge for knowledge tasks in this comparison, averaging 60.8 versus 35.6. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for coding in this comparison, averaging 47.1 versus 18. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for math in this comparison, averaging 84.5 versus 50.4. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for reasoning in this comparison, averaging 78.3 versus 46.6. Inside this category, MuSR is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for agentic tasks in this comparison, averaging 60.2 versus 33.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for multimodal and grounded tasks in this comparison, averaging 66.7 versus 41.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for instruction following in this comparison, averaging 87 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for multilingual tasks in this comparison, averaging 82.8 versus 61.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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