Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
DeepSeekMath V2 is clearly ahead on the aggregate, 66 to 30. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeekMath V2's sharpest advantage is in mathematics, where it averages 84 against 37. The single biggest benchmark swing on the page is HumanEval, 72 to 14.
DeepSeekMath V2 is the reasoning model in the pair, while LFM2.5-1.2B-Instruct is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. DeepSeekMath V2 gives you the larger context window at 128K, compared with 32K for LFM2.5-1.2B-Instruct.
Pick DeepSeekMath V2 if you want the stronger benchmark profile. LFM2.5-1.2B-Instruct only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
DeepSeekMath V2
63.9
LFM2.5-1.2B-Instruct
25.7
DeepSeekMath V2
47.3
LFM2.5-1.2B-Instruct
7.2
DeepSeekMath V2
68.1
LFM2.5-1.2B-Instruct
32.4
DeepSeekMath V2
75.9
LFM2.5-1.2B-Instruct
32.1
DeepSeekMath V2
61
LFM2.5-1.2B-Instruct
26
DeepSeekMath V2
83
LFM2.5-1.2B-Instruct
80
DeepSeekMath V2
82.5
LFM2.5-1.2B-Instruct
60.7
DeepSeekMath V2
84
LFM2.5-1.2B-Instruct
37
DeepSeekMath V2 is ahead overall, 66 to 30. The biggest single separator in this matchup is HumanEval, where the scores are 72 and 14.
DeepSeekMath V2 has the edge for knowledge tasks in this comparison, averaging 61 versus 26. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DeepSeekMath V2 has the edge for coding in this comparison, averaging 47.3 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
DeepSeekMath V2 has the edge for math in this comparison, averaging 84 versus 37. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
DeepSeekMath V2 has the edge for reasoning in this comparison, averaging 75.9 versus 32.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
DeepSeekMath V2 has the edge for agentic tasks in this comparison, averaging 63.9 versus 25.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
DeepSeekMath V2 has the edge for multimodal and grounded tasks in this comparison, averaging 68.1 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
DeepSeekMath V2 has the edge for instruction following in this comparison, averaging 83 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
DeepSeekMath V2 has the edge for multilingual tasks in this comparison, averaging 82.5 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.