Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Sibling matchup inside the GPT-5 family.
GPT-5 (high) and GPT-5 nano sit in the same GPT-5 family. This page is less about two unrelated model lineages and more about how the siblings trade off on benchmark shape, token costs, and practical limits like context window.
GPT-5 (high) is clearly ahead on the aggregate, 84 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5 (high)'s sharpest advantage is in mathematics, where it averages 94 against 85.2. The single biggest benchmark swing on the page is GPQA, 91 to 71.2.
GPT-5 nano gives you the larger context window at 400K, compared with 128K for GPT-5 (high).
GPT-5 (high) makes more sense if mathematics is the priority, while GPT-5 nano is the cleaner fit if you need the larger 400K context window.
GPT-5 (high)
78.3
GPT-5 nano
71.2
GPT-5 (high)
94
GPT-5 nano
85.2
GPT-5 (high) and GPT-5 nano are sibling variants in the GPT-5 family, so the right pick depends on whether you value the better benchmark line, cheaper tokens, or the larger context window. GPT-5 (high) is ahead overall 84 to 31.
GPT-5 (high) has the edge for knowledge tasks in this comparison, averaging 78.3 versus 71.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5 (high) has the edge for math in this comparison, averaging 94 versus 85.2. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
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