Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 2.5 Flash is clearly ahead on the aggregate, 49 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 2.5 Flash's sharpest advantage is in multimodal & grounded, where it averages 67.7 against 32.4. The single biggest benchmark swing on the page is MMMU-Pro, 69 to 27.
Gemini 2.5 Flash is also the more expensive model on tokens at $0.15 input / $0.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2.5-1.2B-Thinking. That is roughly Infinityx on output cost alone. LFM2.5-1.2B-Thinking is the reasoning model in the pair, while Gemini 2.5 Flash 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. Gemini 2.5 Flash gives you the larger context window at 1M, compared with 32K for LFM2.5-1.2B-Thinking.
Pick Gemini 2.5 Flash if you want the stronger benchmark profile. LFM2.5-1.2B-Thinking only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Gemini 2.5 Flash
46.5
LFM2.5-1.2B-Thinking
34.1
Gemini 2.5 Flash
21.7
LFM2.5-1.2B-Thinking
8.2
Gemini 2.5 Flash
67.7
LFM2.5-1.2B-Thinking
32.4
Gemini 2.5 Flash
59.2
LFM2.5-1.2B-Thinking
38.4
Gemini 2.5 Flash
40.5
LFM2.5-1.2B-Thinking
27
Gemini 2.5 Flash
79
LFM2.5-1.2B-Thinking
72
Gemini 2.5 Flash
70.8
LFM2.5-1.2B-Thinking
60.7
Gemini 2.5 Flash
59.4
LFM2.5-1.2B-Thinking
42.3
Gemini 2.5 Flash is ahead overall, 49 to 33. The biggest single separator in this matchup is MMMU-Pro, where the scores are 69 and 27.
Gemini 2.5 Flash has the edge for knowledge tasks in this comparison, averaging 40.5 versus 27. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Gemini 2.5 Flash has the edge for coding in this comparison, averaging 21.7 versus 8.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Gemini 2.5 Flash has the edge for math in this comparison, averaging 59.4 versus 42.3. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Gemini 2.5 Flash has the edge for reasoning in this comparison, averaging 59.2 versus 38.4. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Gemini 2.5 Flash has the edge for agentic tasks in this comparison, averaging 46.5 versus 34.1. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Gemini 2.5 Flash has the edge for multimodal and grounded tasks in this comparison, averaging 67.7 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Gemini 2.5 Flash has the edge for instruction following in this comparison, averaging 79 versus 72. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Gemini 2.5 Flash has the edge for multilingual tasks in this comparison, averaging 70.8 versus 60.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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