vllm-project/recipes

Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services

Cook up amazing AI applications effortlessly with MiniCPM / MiniCPM-V / MiniCPM-o

Community recipes for serving LLMs on RTX 3090/4090/5090 CUDA gpus. Multi-engine (vLLM, llama.cpp, ik_llama) and model-agnostic. Currently shipping Qwen3.6-27B Qwen3.6 35B Gemma 4 26B Gemma 4 31B configs for 1× and 2× cards.

The Runpod worker template for serving our large language model endpoints. Powered by vLLM.

LMDeploy is a toolkit for compressing, deploying, and serving LLMs.

A modern web interface for managing and interacting with vLLM servers (www.github.com/vllm-project/vllm). Supports both GPU and CPU modes, with special optimizations for macOS Apple Silicon and enterprise deployment on OpenShift/Kubernetes.

Recipes to scale inference-time compute of open models

A collection of notebooks/recipes showcasing usecases of open-source models with Together AI.