Together AI
AI Infrastructure & MLOps
Build what's next on the AI Native Cloud. Full-stack AI platform for inference, fine-tuning, and GPU clusters — powered by cutting-edge research.
Together AI is an open-source, full-stack AI platform designed for developers and organizations building AI applications. The platform provides integrated tools for inference, fine-tuning, and GPU cluster management, enabling users to deploy and optimize large language models and other AI workloads. The platform serves multiple user personas, including machine learning engineers seeking flexible infrastructure, researchers requiring access to computational resources, and developers building AI-native applications. Together AI is particularly suited for teams that need control over their model deployment pipeline and want to avoid vendor lock-in through open-source tooling. Key capabilities include support for running inference on various model architectures, fine-tuning models on custom datasets, and orchestrating distributed GPU clusters for scaled workloads. The platform is built on research-driven principles, incorporating advances in efficient model serving and training. As an open-source offering, Together AI enables users to self-host infrastructure and modify the platform to fit specific requirements. This approach provides transparency in how models are served and processed, which appeals to organizations with data privacy concerns or specific compliance needs. Together AI positions itself within the broader AI infrastructure ecosystem, competing alongside other platforms that offer modular approaches to model deployment and training rather than monolithic solutions.
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Run and deploy AI models with a cloud API
Serve and scale open-source and custom AI models on the fastest, most reliable inference platform.
The AI community platform for models and datasets
Hey HN! I'm Fabio and I built UltraContext, a simple context API for AI agents with automatic versioning. After two years building AI agents in production, I experienced firsthand how frustrating it is to manage context at scale. Storing messages, iterating system prompts, debugging behavior an
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