How do I self-host Qwen 2.5?

Qwen 2.5 can be deployed using Docker Compose. The AltStack provides a production-ready configuration that you can deploy on your own server. Simply copy the configuration and run it on any machine with Docker installed.

What are the system requirements for self-hosting Qwen 2.5?

The recommended hardware for Qwen 2.5 is: 8GB VRAM (7B), 40GB+ VRAM (32B), 140GB+ VRAM (72B). Actual requirements may vary based on usage volume and data size.

Is Qwen 2.5 free to self-host?

Yes, Qwen 2.5 is open source under the Apache License 2.0 and free to self-host. Your only costs are the server infrastructure. A basic cloud VPS starts at around $5-10/month.

What programming language is Qwen 2.5 built with?

Qwen 2.5 is built with Python. It has 27,665 stars on GitHub, indicating strong community adoption and support.

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Deploy Qwen 2.5

Comprehensive LLM series from Alibaba Cloud, excelling in coding, math, and multilingual support.

Quick Start

Create a directory

mkdir qwen-self-hosted && cd qwen-self-hosted

Create config file

Copy the content from the Config tab below into a file named docker-compose.yml

Deploy

docker compose up -d

Fast Track

Deploy Qwen 2.5 in Minutes

Use our optimized Docker templates to deploy Qwen 2.5 on any cloud provider. Get $200 in free credit to start on DigitalOcean.

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$200

Metadata

License

Apache License 2.0

Language

Python

Last Updated

1/9/2026

Configuration

yaml

services:
  ollama:
    image: ollama/ollama:latest
    container_name: ollama-qwen
    restart: unless-stopped
    ports:
      - "11434:11434"
    volumes:
      - ollama_data:/root/.ollama
    # Uncomment for GPU support:
    # deploy:
    #   resources:
    #     reservations:
    #       devices:
    #         - driver: nvidia
    #           count: all
    #           capabilities: [gpu]
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:11434"]
      interval: 30s
      timeout: 10s
      retries: 3
    entrypoint: ["/bin/sh", "-c", "ollama serve & sleep 5 && ollama pull qwen2.5 && wait"]

volumes:
  ollama_data:

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