---
id: "b634"
language: "en"
library: "tools"
official_url: "https://docs.vllm.ai/en/latest/"
profile_updated_on: "2026-10-22"
---

# vLLM

Serve language models with KV-cache management, continuous batching, quantization and multi-device parallelism.

- Company / organization: vLLM Project
- Category: Model development
- Official website: [https://docs.vllm.ai/en/latest/](https://docs.vllm.ai/en/latest/)
- Profile updated: 2026-10-22


## Overview

vLLM is an open-source engine for language-model inference and serving. Configure a model and hardware to generate in batches or run an API server for application requests. PagedAttention, continuous batching and prefix caching manage inference memory and scheduling; quantization, structured outputs and distributed inference are also supported. It does not supply model weights or hosted compute. Compatibility and performance depend on the model, backend and configuration.

## Official sources and references

- [Official website](https://docs.vllm.ai/en/latest/)

## Update history

### vLLM releases v0.32.0

2026-10-18

Adds structured decisions, generic parsers and broader low-precision KV caches, with model- and hardware-specific requirements.

[vLLM](https://github.com/vllm-project/vllm/releases/tag/v0.32.0)

## Reading & subscriptions

- [Interactive profile](../../../products/vllm--b634.html)
- [Read](../../../read/en/products/vllm--b634.html)
- [JSON](../../../read/en/products/vllm--b634.json)

Descriptions summarize public information; consult official websites for features, pricing and regional availability.