vLLM
Fast LLM inference and serving library with PagedAttention, continuous batching and an OpenAI-compatible server.
Apache-2.0 serving engine for NVIDIA, AMD and Intel GPUs and CPUs.
vLLM is a library and server for running large language models at high throughput. It suits teams serving open models to many users on their own GPUs.
What it is
vLLM uses PagedAttention, continuous batching, chunked prefill and prefix caching, with quantization formats such as FP8, GPTQ, AWQ and GGUF. It serves an OpenAI-compatible API, plus Anthropic Messages API and gRPC, on NVIDIA, AMD and Intel GPUs and several CPU types.
Who it's for
It suits engineers running inference at scale who can manage GPU drivers and model downloads. It does not suit casual local chat, where Ollama or llama.cpp are simpler.
Key features
PagedAttention
Efficient attention key and value memory management.
Continuous batching
Chunked prefill and prefix caching for throughput.
OpenAI-compatible server
Plus Anthropic Messages API and gRPC support.
Broad quantization
FP8, INT4, GPTQ, AWQ, GGUF and more.
Wide hardware
NVIDIA, AMD, Intel GPUs and x86, ARM, PowerPC CPUs.
Multi-LoRA
Efficient multi-LoRA for dense and MoE layers.
Up and running in 3 steps
Our honest verdict
What's great
- Built for serving many concurrent requests.
- Apache-2.0 licensing.
- Hardware plugins cover TPUs, Gaudi, Ascend and Apple silicon.
- Install is one command: uv pip install vllm.
Where it falls short
- You need supported GPUs, drivers and large model downloads.
- Tuning for throughput takes expertise.
- Overkill for single-user local use.
Pricing & license
vLLM is free under Apache-2.0. There is no paid plan on its README; the cost is the GPUs or cloud instances you run it on.
Open remote AI-training roles
870 open remote AI-training roles, updated November 14, 2026; most pay $20–$170 an hour. Zekai lists them free; the application goes to the employer’s platform.
Alternatives
These reviewed AI tools do the same job instantly — from our scored directory.
Use it, or have us set it up
FAQ
What hardware does it support?
NVIDIA, AMD and Intel GPUs and x86, ARM and PowerPC CPUs, with plugins for TPUs and others.
Does it offer an OpenAI-compatible API?
Yes, plus Anthropic Messages API and gRPC.
Is it easy for beginners?
No; it targets people serving models on GPUs.
