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vLLM Ascend

High-throughput LLM serving on Huawei Ascend NPUs. Community-maintained hardware plugin for vLLM.

★ 2,621 GitHub Apache-2.0 vllmascendhuaweinpullm-inferenceinference LLM & Chat

Overview

vLLM Ascend is a community-maintained hardware plugin that brings the vLLM inference engine to Huawei Ascend NPUs. It lets you serve large language models with high throughput and low latency on Ascend 910B and 310P hardware, offering a cost-effective, energy-efficient alternative to NVIDIA GPUs for self-hosted LLM deployments. The project is actively developed by the vLLM community, supports the latest vLLM versions through Ascend's vllm-ascend companion package, and ships with an official Docker image for quick starts.

Requirements

Min vCPU
2
Min RAM
8192 MB
Min Disk
10 GB
Rec vCPU
8
Rec RAM
32768 MB
Rec Disk
20 GB

Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  vllm-ascend:
    image: ascendai/vllm-ascend:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/vllm-ascend:/data

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