Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 2.5 Pro is clearly ahead on the aggregate, 72 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.05 input / $0.40 output per 1M tokens for GPT-5 nano. That is roughly 12.5x on output cost alone. GPT-5 nano is the reasoning model in the pair, while Gemini 2.5 Pro 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 Pro gives you the larger context window at 1M, compared with 400K for GPT-5 nano.
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. GPT-5 nano only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Gemini 2.5 Pro
67.5
GPT-5 nano
71.2
Gemini 2.5 Pro
83.1
GPT-5 nano
85.2
Gemini 2.5 Pro is ahead overall, 72 to 31. The biggest single separator in this matchup is GPQA, where the scores are 83 and 71.2.
GPT-5 nano has the edge for knowledge tasks in this comparison, averaging 71.2 versus 67.5. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5 nano has the edge for math in this comparison, averaging 85.2 versus 83.1. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
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