Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3.1 Flash-Lite is clearly ahead on the aggregate, 55 to 51. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for Gemini 3.1 Flash-Lite. That is roughly 150.0x on output cost alone. o1 is the reasoning model in the pair, while Gemini 3.1 Flash-Lite 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 3.1 Flash-Lite gives you the larger context window at 1M, compared with 200K for o1.
Pick Gemini 3.1 Flash-Lite if you want the stronger benchmark profile. o1 only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Gemini 3.1 Flash-Lite
51.2
o1
83.8
Gemini 3.1 Flash-Lite
32.7
o1
41
Gemini 3.1 Flash-Lite
63.1
o1
74.3
Gemini 3.1 Flash-Lite
79
o1
92.2
Gemini 3.1 Flash-Lite is ahead overall, 55 to 51. The biggest single separator in this matchup is MMLU, where the scores are 63 and 91.8.
o1 has the edge for knowledge tasks in this comparison, averaging 83.8 versus 51.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o1 has the edge for coding in this comparison, averaging 41 versus 32.7. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
o1 has the edge for math in this comparison, averaging 74.3 versus 63.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o1 has the edge for instruction following in this comparison, averaging 92.2 versus 79. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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