Hugging Face 开源模型算力价值估算已接近 10 亿美元
Hugging Face 联合创始人算了笔账：30 多家实验室开源模型堆出了近 10 亿美元算力，还有个网站能自己查数据。
Hugging Face 联合创始人 Thom Wolf 估算，Meta、NVIDIA、Alibaba、DeepSeek、Moonshot、Mistral 等 30 多家实验室在 Hugging Face Hub 上开源模型的训练算力总价值已接近 10 亿美元，可免费下载。
2023 年底这一数字还不到 4000 万美元，两年内增长约 25 倍。估算中约一半来自官方公布的算力数据，其余为推测，且未计入约 90 万个社区微调模型。
作者类比维基百科由志愿者工时写成，称这批开源模型是 GPU 工时和数据写成的公共资源。
Fun and crazy napkin math: Meta, NVIDIA, Alibaba, DeepSeek, Moonshot, Mistral and ~30 other labs have shared close to $1B worth of training compute on the Hugging Face Hub Free to download End of 2023 it was under $40M Wikipedia was written in volunteer hours. This AI age commons is written in GPU-hours and data (it's a floor btw: about half comes from official compute numbers rest is educated guess and it still miss the ~900k community fine-tunes) Space with data to explore: thomwolf-hub-dollars.static.hf.space📊 30 ⚡
This report is categorized under AITOP's "Industry" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows and US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include Hugging Face, DeepSeek, Mistral, 开源模型.
Source attribution: curated from Thomas Wolf (@Thom_Wolf). Cross-source corroboration: 11 independent sources have covered this development (including NVIDIA AI, Gorden Sun, rohanpaul_ai), confirming industry-wide signal strength.
