Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek LLM 2.0 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.
DeepSeek LLM 2.0's sharpest advantage is in mathematics, where it averages 80.8 against 50.4. The single biggest benchmark swing on the page is AIME 2023, 80 to 46.
DeepSeek LLM 2.0 gives you the larger context window at 128K, compared with 32K for LFM2-24B-A2B.
Pick DeepSeek LLM 2.0 if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
DeepSeek LLM 2.0
57.9
LFM2-24B-A2B
33.4
DeepSeek LLM 2.0
42.9
LFM2-24B-A2B
18
DeepSeek LLM 2.0
64.5
LFM2-24B-A2B
41.7
DeepSeek LLM 2.0
73.6
LFM2-24B-A2B
46.6
DeepSeek LLM 2.0
57.5
LFM2-24B-A2B
35.6
DeepSeek LLM 2.0
85
LFM2-24B-A2B
68
DeepSeek LLM 2.0
78.8
LFM2-24B-A2B
61.4
DeepSeek LLM 2.0
80.8
LFM2-24B-A2B
50.4
DeepSeek LLM 2.0 is ahead overall, 62 to 38. The biggest single separator in this matchup is AIME 2023, where the scores are 80 and 46.
DeepSeek LLM 2.0 has the edge for knowledge tasks in this comparison, averaging 57.5 versus 35.6. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for coding in this comparison, averaging 42.9 versus 18. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for math in this comparison, averaging 80.8 versus 50.4. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for reasoning in this comparison, averaging 73.6 versus 46.6. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for agentic tasks in this comparison, averaging 57.9 versus 33.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for multimodal and grounded tasks in this comparison, averaging 64.5 versus 41.7. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for instruction following in this comparison, averaging 85 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for multilingual tasks in this comparison, averaging 78.8 versus 61.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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