Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Llama 4 Scout is clearly ahead on the aggregate, 42 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5 nano is also the more expensive model on tokens at $0.05 input / $0.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 4 Scout. That is roughly Infinityx on output cost alone. GPT-5 nano is the reasoning model in the pair, while Llama 4 Scout 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. Llama 4 Scout gives you the larger context window at 10M, compared with 400K for GPT-5 nano.
Pick Llama 4 Scout if you want the stronger benchmark profile. GPT-5 nano only becomes the better choice if mathematics is the priority or you want the stronger reasoning-first profile.
Llama 4 Scout
38.7
GPT-5 nano
71.2
Llama 4 Scout
47.4
GPT-5 nano
85.2
Llama 4 Scout is ahead overall, 42 to 31. The biggest single separator in this matchup is AIME 2025, where the scores are 48 and 85.2.
GPT-5 nano has the edge for knowledge tasks in this comparison, averaging 71.2 versus 38.7. 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 47.4. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
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