COG — Package and deploy machine learning models

COG is an open-source tool that packages machine learning models into production-ready containers for ML engineers.

COG is an open-source tool that packages machine learning models into standard Docker containers for consistent deployment. It is designed specifically for machine learning engineers and data scientists who need to move research models into production environments without managing complex Dockerfiles. By using a simple YAML configuration, COG automates the creation of a container that includes all necessary dependencies, system libraries, and GPU configurations. The tool ensures that your ML models run identically on a local machine, a remote server, or within a cloud infrastructure. COG automatically generates an HTTP server using FastAPI, providing a clear API for model predictions without manual coding. This standardization allows teams to focus on model logic rather than infrastructure management. Business owners can find more technical resources and similar 2026 deployment tools on surfai.app to optimize their technical stack. Using COG facilitates better collaboration between data science teams and DevOps engineers by providing a unified packaging format. It handles the nuances of GPU drivers and CUDA versions, which are frequent pain points in machine learning scaling. The tool also supports automatic generation of OpenAPI schemas, making it easier for backend developers to integrate ML features into existing applications. As an open-source project managed by Replicate, COG is free to use for local development and self-hosting. Organizations looking for managed scaling can deploy these containers directly to Replicate's cloud infrastructure on a usage-based pricing model.

• Pricing: freemium

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