Qwenの30億ダウンロードとHugging Faceの公開データとの差

"Alibaba Group Holding’s open-weight models have accumulated more than 3 billion global downloads in the past six months, eclipsing Meta Platforms Inc., Alphabet Inc. and domestic peers to become the world’s No. 1 artificial-intelligence model."／"Qwen, Alibaba’s family of AI models, has open-sourced more than 460 models and its ecosystem has spawned 300,000-plus derivatives, the Chinese technology company said in an emailed statement."／"Google, part of Alphabet, had 418 million downloads while Meta stood at 227 million in 2026, according to popular open-source AI hub Hugging Face Inc."— Fortune の報道より

"Moonshot’s frontier-only portfolio recorded 37M downloads over the year, while Qwen’s broader release strategy across model sizes reached 2,045M (across repositories with declared parameter counts, 2,061M including all repositories) , about 55 times more."（2. Attention ≠ Adoption）／"This analysis is based on activity observed on the Hugging Face Hub during the first seven months of 2026."／"Downloads indicate usage within the Hub ecosystem, but they do not capture API usage, private deployments, or models distributed through other channels."（いずれも Notes on method）— Hugging Face 公式ブログより

"Qwen-based models now account for 151,448 derivatives on the Hub, 2.6× Meta’s total footprint and 4.7× the Llama repositories specifically. Google follows with 82,506 derivatives."／"Qwen derivatives have increased at roughly 180–210 new repositories per day throughout the first seven months of 2026"／"Even among the 28,531 GGUF conversions of Qwen models on the Hub, Qwen published only 54."（いずれも 4. Qwen has become the community's base model）／"And that route runs on Qwen: 39.6 million GGUF downloads a month, nearly twice Gemma's 20.8 million and more than five times Llama's 7.5 million. The Llama gap is not a supply problem, Llama-derived GGUF repositories slightly outnumber Qwen's. Same shelf space, a fifth of the traffic."（5. Small models remain the practical layer）— Hugging Face 公式ブログより

"The metrics used in this report, including downloads, likes, derivatives, and model releases, represent different aspects of ecosystem activity. They should not be interpreted as direct measures of model quality, commercial adoption, or overall market share."／"Because open-source AI adoption happens across many channels, Hub activity should be viewed as one perspective on ecosystem development rather than a complete measurement of the AI market."（いずれも Notes on method）— Hugging Face 公式ブログより