Open WebUI

Run LLMs locally with one command

Tool for running large language models locally on your machine with a simple CLI interface. Download and run Llama 3, Mistral, Gemma, Phi, Code Llama, and dozens of other open-source models with a single command. Features model management, GPU acceleration (NVIDIA/AMD/Apple Silicon), OpenAI-compatible API server, Modelfile for customization, and multi-model switching. Ideal for offline AI development, privacy-sensitive use cases, and local testing. 120K+ GitHub stars.

Run local LLMs with an intuitive desktop GUI and OpenAI-compatible API server.

Free desktop application by Element Labs for discovering, downloading, and running open-source LLMs locally. Features a curated Hugging Face model browser, side-by-side model comparison, parameter tuning, and an OpenAI-compatible API server on localhost:1234. Powered by llama.cpp with Metal acceleration for Apple Silicon.

Open-source AI second brain with deep research and RAG

Khoj is an open-source personal AI app that serves as a self-hostable second brain. It connects to your documents — PDFs, Markdown, Notion, Word — and uses RAG to answer questions grounded in your knowledge base. Supports any local or cloud LLM including Llama, Claude, GPT, and Gemini. Features custom agents, scheduled automations, deep research mode, semantic search, and Obsidian, Emacs, and WhatsApp integrations. Over 33,000 GitHub stars, YC-backed.

Self-hosted AI platform with RAG, agents, and 40+ connectors

Onyx is an open-core, self-hostable AI knowledge platform for enterprise search, RAG chat, deep research, custom agents, and workplace connectors. It connects to 40+ apps, supports permission-aware retrieval, and offers Cloud, Docker/Kubernetes, and enterprise deployment paths for teams that need controlled internal AI search.

Heterogeneous CPU-GPU inference and SFT for large MoE models

Open-source framework for running and fine-tuning large Mixture-of-Experts models with heterogeneous CPU-GPU execution, optimized kernels, limited VRAM and SGLang or LLaMA-Factory integrations.

Official Kubernetes and Helm reference stack built on the vLLM inference engine

Official vLLM reference implementation for scaling the existing inference engine on Kubernetes with Helm, request routing, KV-cache offload, autoscaling and Prometheus/Grafana observability.

Distributed inference orchestration above vLLM, SGLang and TensorRT-LLM

Open-source, datacenter-scale orchestration layer that coordinates vLLM, SGLang and TensorRT-LLM across nodes with disaggregated serving, KV-aware routing, multi-tier cache management and automatic scaling.

Open-source GPU control plane for scalable AI model serving

Open-source GPU cluster manager that configures vLLM, SGLang, TensorRT-LLM or custom engines, serves models through compatible APIs, and provisions SSH-accessible GPU instances across on-premises, Kubernetes and cloud environments.

Disaggregated KV cache storage and transfer for LLM serving

Open-source infrastructure for disaggregated LLM serving that pools KV caches across prefill and decode workers, with high-performance transfer, distributed storage and integrations for vLLM and SGLang.

Reusable KV cache infrastructure for scalable LLM inference

Open-source KV cache management layer that persists, offloads and reuses model key-value caches across requests and serving engines to reduce repeated prefill work and improve inference throughput.