Everything in the catalog

Runs open models locally or in the cloud, with a REST API and Python and JavaScript libraries.

Fast, easy-to-use open-source library for LLM inference and serving, with an OpenAI-compatible server.

Plain C/C++ LLM inference engine that runs quantized models on many hardware backends, with an OpenAI-compatible server.

Open-source AI runtime that runs text, voice, image and agent workloads on your own hardware behind OpenAI-compatible APIs.

Managed Ray platform for distributed training, batch inference and data processing on GPU clusters.

Open-source inference framework for LLMs and multimodal models, built for agentic workloads and large-scale serving.

Single-file executable that bundles llama.cpp with Cosmopolitan Libc, so an LLM runs locally with no installation.

Hosted API for running, fine-tuning and deploying AI models, including image, video, speech, music and LLMs.

Open-source platform for serving LLM, embedding and multimodal models on your own premises or in the cloud.

Unified inference platform for deploying and scaling AI models on any cloud, with an open-source Python serving framework.

Inference and training platform for hosted and dedicated models, deployable in your cloud or Baseten's.

Open-source library that optimizes LLM and visual generation inference with specialized kernels and a Python framework.

Cloud GPU platform for AI with pods, pay-per-second serverless endpoints and clusters across 31 regions.

Open-source, datacenter-scale orchestration layer that coordinates multi-node inference across engines such as SGLang, TensorRT-LLM and vLLM.