OmniFood-Bench - Nutritional Profile (Homemade Food): leaderboard

OmniFood-Bench asks vision-language models to estimate the macronutrient grams of a pictured meal. This board covers images of home-cooked dishes and is scored as mean absolute percentage error, so lower is better and the value is unbounded above.

Metric: Nutritional-profile MAPE (%; mean absolute percentage error of the predicted macronutrient grams of Homemade Food images, lower is better and unbounded above; images of the MM-Food-100K subset; zero-shot, one standardized prompt per task; the open-weight models see all 1,208 samples and the proprietary models a 496-sample subset). Source: arxiv.org. Saturation forecast: Around May 2027. 6 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.149.17#229
2Claude Sonnet 461.22#400
3Gemini 3 Flash114.28#164

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=omnifood-bench-nutritional-profile-homemade-food · How It Works · Data refreshed daily, snapshot 2026-11-13.