Scarf has launched a daily index that ranks AI model providers and inference platforms across the open-source ecosystem using organisation-level package download activity.
Scarf has launched the Open Source AI Popularity Leaderboard, a public index that ranks AI model providers and inference platforms based on package downloads by organisations. Updated daily, the leaderboard provides a cross-registry view of how AI technologies are being adopted across the open-source ecosystem.
The index is based on Scarf’s processing of billions of open-source package installations. From nearly 700,000 monitored packages, Scarf identifies AI-related packages and maps them to their respective model and inference providers. Each organisation is counted once per day, regardless of how many packages it downloads, helping prevent large-scale installations or automated activity from distorting the rankings.
The leaderboard separates model providers from inference platforms. Model providers are companies that create and distribute AI models using open-source packages, while inference platforms provide services for hosting or running those models. Organisations can appear in either or both categories depending on their products. Scarf collects the underlying data through its gateway and package-registry integrations.
The first leaderboard snapshot shows OpenAI leading package adoption, while Amazon occupies two of the top four positions among inference platforms through Amazon Bedrock and Amazon SageMaker. Ollama ranks sixth among inference platforms, while other providers show differences between their technological capabilities and package-level adoption.
Importantly, the leaderboard measures package adoption rather than direct model usage. It does not account for API requests, token counts, provider revenue, model performance or the specific models used for general-purpose inference. Scarf therefore describes the index as a directional measure of open-source package adoption rather than a measure of the entire AI market.
