Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 2.5 Flash is clearly ahead on the aggregate, 49 to 43. 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 mathematics, where it averages 51.9 against 26.4. The single biggest benchmark swing on the page is MMLU, 50 to 90.2. GPT-4.1 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.15 input / $0.60 output per 1M tokens for Gemini 2.5 Flash. That is roughly 13.3x on output cost alone.
Pick Gemini 2.5 Flash if you want the stronger benchmark profile. GPT-4.1 only becomes the better choice if knowledge is the priority.
Gemini 2.5 Flash
42.7
GPT-4.1
78.3
Gemini 2.5 Flash
27.7
GPT-4.1
54.6
Gemini 2.5 Flash
51.9
GPT-4.1
26.4
Gemini 2.5 Flash
79
GPT-4.1
87.4
Gemini 2.5 Flash is ahead overall, 49 to 43. The biggest single separator in this matchup is MMLU, where the scores are 50 and 90.2.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 78.3 versus 42.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for coding in this comparison, averaging 54.6 versus 27.7. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Gemini 2.5 Flash has the edge for math in this comparison, averaging 51.9 versus 26.4. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for instruction following in this comparison, averaging 87.4 versus 79. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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