vLLM Project

vLLM

High-throughput GPU serving with an OpenAI-compatible API out of the box.

High-throughput GPU serving

Visit Site View on GitHub Read the Docs

GitHub Stars

84.6K

Contributors

2.9K

PyPI / Month

5.6M

Maintained by: vLLM Project
First released: Jun 2023
Last commit: Today
Language: Python
License: Apache 2.0

Strengths

Highest throughput of the open serving engines for busy production workloads.
Drop-in OpenAI-compatible API, so existing clients work unchanged.
Scales across multiple GPUs with tensor and pipeline parallelism.

Trade-offs

Built for GPUs. CPU and Apple Silicon support is limited.
More moving parts to tune than a one-line desktop runner.

Key Features

What the engine gives you out of the box, in plain language.

OpenAI-Compatible API
NVIDIA GPU
AMD GPU
Apple Silicon
CPU Inference
Quantization
Continuous Batching
Multi-GPU
Desktop GUI
One-Line Install
Structured Output
Streaming

PagedAttention
A smarter way to manage GPU memory that fits more concurrent requests on the same card.
Continuous batching
New requests join the batch as soon as a slot frees up, keeping the GPU busy.
OpenAI-compatible server
Expose a local endpoint that mirrors the OpenAI API for chat and completions.

Where It Shines

The jobs this engine is best suited for.

Production model serving
Serve an open model to a real app with high request volume and low cost per token.
Self-hosted OpenAI replacement
Point an existing OpenAI client at your own GPU box and keep data in house.
Multi-GPU deployments
Split a large model across several GPUs when it will not fit on one.

Side-by-Side

Compare vLLM With Another Engine

Add a second or third engine and see stars, downloads, and capabilities lined up next to each other.

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Frequently Asked Questions

What Is an Inference Engine?

An inference engine is the software that runs a language model and turns your prompt into tokens. It loads the model weights, manages memory on your GPU or CPU, and serves the output, usually behind an API.

Is vLLM open source?

vLLM ships under the Apache 2.0 license. The source code lives on GitHub, so you can read it, fork it, and run it on your own hardware if your team prefers self-hosting.

Which language is vLLM built in?

vLLM is primarily a Python project. The implementation language matters less than the hardware it supports and the throughput it delivers, but it does affect how easily your team can extend or debug it.

Free Monthly Report

The AI Build Report

The state of AI models, API prices, and what to run where. New every month, free.

vLLM Project

vLLM

High-throughput GPU serving with an OpenAI-compatible API out of the box.

High-throughput GPU serving

Visit Site View on GitHub Read the Docs

GitHub Stars

84.6K

Contributors

2.9K

PyPI / Month

5.6M

Maintained by: vLLM Project
First released: Jun 2023
Last commit: Today
Language: Python
License: Apache 2.0

Strengths

Highest throughput of the open serving engines for busy production workloads.
Drop-in OpenAI-compatible API, so existing clients work unchanged.
Scales across multiple GPUs with tensor and pipeline parallelism.

Trade-offs

Built for GPUs. CPU and Apple Silicon support is limited.
More moving parts to tune than a one-line desktop runner.

Key Features

What the engine gives you out of the box, in plain language.

OpenAI-Compatible API
NVIDIA GPU
AMD GPU
Apple Silicon
CPU Inference
Quantization
Continuous Batching
Multi-GPU
Desktop GUI
One-Line Install
Structured Output
Streaming

PagedAttention
A smarter way to manage GPU memory that fits more concurrent requests on the same card.
Continuous batching
New requests join the batch as soon as a slot frees up, keeping the GPU busy.
OpenAI-compatible server
Expose a local endpoint that mirrors the OpenAI API for chat and completions.

Where It Shines

The jobs this engine is best suited for.

Production model serving
Serve an open model to a real app with high request volume and low cost per token.
Self-hosted OpenAI replacement
Point an existing OpenAI client at your own GPU box and keep data in house.
Multi-GPU deployments
Split a large model across several GPUs when it will not fit on one.

Side-by-Side

Compare vLLM With Another Engine

Add a second or third engine and see stars, downloads, and capabilities lined up next to each other.

Open the Comparator

Frequently Asked Questions

What Is an Inference Engine?

Is vLLM open source?

vLLM ships under the Apache 2.0 license. The source code lives on GitHub, so you can read it, fork it, and run it on your own hardware if your team prefers self-hosting.

Which language is vLLM built in?

Free Monthly Report

The AI Build Report

The state of AI models, API prices, and what to run where. New every month, free.

vLLM

Strengths

Trade-offs

Key Features

PagedAttention

Continuous batching

OpenAI-compatible server

Where It Shines

Production model serving

Self-hosted OpenAI replacement

Multi-GPU deployments

Compare vLLM With Another Engine

Frequently Asked Questions

What Is an Inference Engine?

Is vLLM open source?

Which language is vLLM built in?

The AI Build Report

vLLM

Strengths

Trade-offs

Key Features

PagedAttention

Continuous batching

OpenAI-compatible server

Where It Shines

Production model serving

Self-hosted OpenAI replacement

Multi-GPU deployments

Compare vLLM With Another Engine

Frequently Asked Questions

What Is an Inference Engine?

Is vLLM open source?

Which language is vLLM built in?

The AI Build Report