Best Open Source LLM Runtimes

A high-throughput and memory-efficient inference and serving engine for LLMs

Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Making large AI models cheaper, faster and more accessible

Machine Learning Engineering Open Book

Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.

OpenVINO™ is an open source toolkit for optimizing and deploying AI inference

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.

Swap GPT for any LLM by changing a single line of code. Xinference lets you run open-source, speech, and multimodal models on cloud, on-prem, or your laptop — all through one unified, production-ready inference API.

Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU.