Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeek V3.1 is clearly ahead on the aggregate, 35 to 30. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V3.1's sharpest advantage is in reasoning, where it averages 40.7 against 32.1. The single biggest benchmark swing on the page is IFEval, 67 to 80. LFM2.5-1.2B-Instruct does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
DeepSeek V3.1 gives you the larger context window at 128K, compared with 32K for LFM2.5-1.2B-Instruct.
Pick DeepSeek V3.1 if you want the stronger benchmark profile. LFM2.5-1.2B-Instruct only becomes the better choice if instruction following is the priority.
DeepSeek V3.1
32.9
LFM2.5-1.2B-Instruct
25.7
DeepSeek V3.1
14.8
LFM2.5-1.2B-Instruct
7.2
DeepSeek V3.1
39.5
LFM2.5-1.2B-Instruct
32.4
DeepSeek V3.1
40.7
LFM2.5-1.2B-Instruct
32.1
DeepSeek V3.1
30.5
LFM2.5-1.2B-Instruct
26
DeepSeek V3.1
67
LFM2.5-1.2B-Instruct
80
DeepSeek V3.1
60.8
LFM2.5-1.2B-Instruct
60.7
DeepSeek V3.1
44.2
LFM2.5-1.2B-Instruct
37
DeepSeek V3.1 is ahead overall, 35 to 30. The biggest single separator in this matchup is IFEval, where the scores are 67 and 80.
DeepSeek V3.1 has the edge for knowledge tasks in this comparison, averaging 30.5 versus 26. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DeepSeek V3.1 has the edge for coding in this comparison, averaging 14.8 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
DeepSeek V3.1 has the edge for math in this comparison, averaging 44.2 versus 37. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
DeepSeek V3.1 has the edge for reasoning in this comparison, averaging 40.7 versus 32.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
DeepSeek V3.1 has the edge for agentic tasks in this comparison, averaging 32.9 versus 25.7. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
DeepSeek V3.1 has the edge for multimodal and grounded tasks in this comparison, averaging 39.5 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
LFM2.5-1.2B-Instruct has the edge for instruction following in this comparison, averaging 80 versus 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
DeepSeek V3.1 has the edge for multilingual tasks in this comparison, averaging 60.8 versus 60.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.