Noesion Radarnoesion.ai
Research2026-08-03

The ATOM Project, led by Nathan Lambert of Interconnects.ai, published the Relative Adoption Metric (RAM), which normalizes HuggingFace download counts of open-weight models against a size-class baseline. A model's RAM score divides its cumulative downloads at a given age (7, 14, 30, 60, 90, 180 or 365 days after release) by the download count of the 10th-most-downloaded model of the same parameter class at the same age; a score above 1 means the model is tracking toward top-10 status for its size. The stated motivation is that small models dominate raw counts: of roughly 2 billion downloads across 1,100+ tracked LLMs, more than 1.4 billion come from the 1-9B range, partly due to CI and automated pulls. Published figures (baseline 2026-Q2, snapshot 2026-05-23) show GPT-OSS 120B at 21.68x at 90 days, GLM-5 peaking at 20.21x at 30 days, Kimi K2.5 rising to 9.55x at 90 days, while DeepSeek V3.2 (0.46-0.59x) and GLM 4.7 (~0.65x) sit below baseline.

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