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  • vLLM
    vLLM is a fast and easy-to-use library for LLM inference and serving Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry
  • GitHub - vllm-project vllm: A high-throughput and memory-efficient . . .
    vLLM is a fast and easy-to-use library for LLM inference and serving Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry
  • 快速开始 | vLLM 中文站
    OpenAI 兼容服务器 vLLM 可以部署为实现 OpenAI API 协议的服务器。 这使得 vLLM 可以作为使用 OpenAI API 的应用程序的直接替代品。 默认情况下，服务器在 http: localhost:8000 启动。 您可以使用 --host 和 --port 参数指定地址。
  • VLLM 部署 GLM-5 实践指南 - 探索云原生
    本文将详细介绍如何使用 vLLM 框架在生产环境中部署 GLM-5 模型。 根据各大榜单排名以及实测表现，GLM-5 在多项评测中表现出色，是当前开源模型中的佼佼者。 本文涵盖以下内容： 模型下载：FP8 和 INT4 两种量化版本 镜像构建：构建支持 GLM-5 的 vLLM 镜像
  • vLLM - vLLM 文档
    vLLM 是一个用于 LLM 推理和服务的快速易用的库。 vLLM 最初是在加州大学伯克利分校的 Sky Computing Lab 开发的，现已发展成为一个社区驱动的项目，融合了学术界和工业界的贡献。 如何开始使用 vLLM 取决于您的用户类型。 如果您打算
  • vLLM - OpenClaw
    vLLM can serve open-source (and some custom) models via an OpenAI-compatible HTTP API OpenClaw can connect to vLLM using the openai-completions API OpenClaw can also auto-discover available models from vLLM when you opt in with VLLM_API_KEY (any value works if your server doesn’t enforce auth) and you do not define an explicit models providers vllm entry
  • vLLM for Inference | DGX Spark
    vLLM is an inference engine designed to run large language models efficiently The key idea is maximizing throughput and minimizing memory waste when serving LLMs
  • vLLM Tutorial: The Ultimate Beginners Guide to Serving LLMs
    Learn how to use vLLM for high-throughput LLM inference This vLLM tutorial covers installation, Python coding, OpenAI API serving, and performance tuning
  • Ollama vs vLLM: Which Should You Use to Self-Host LLMs?
    Ollama and vLLM both run LLMs on your own hardware, but for different jobs Here's how they compare on performance, ease of setup, and when to use each
  • I shipped Googles TurboQuant as a vLLM plugin 72 hours after the paper . . .
    Posted on Mar 27 • Originally published at alberto codes I shipped Google's TurboQuant as a vLLM plugin 72 hours after the paper — here's what nobody else tested # python # gpu # ai # machinelearning Google published TurboQuant at ICLR 2026 — a technique that compresses transformer KV caches to 4 bits per coordinate with zero accuracy loss





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