AI/ML
How to Deploy WAN 2.1 on AWS EC2 - A Complete Guide
Introduction
Alibaba released Wan 2.1's T2V-14B model on February 25, 2025, and it needs strong computation to produce high quality videos. Targeting developers in need of scalable solutions, this guide describes its implementation on Amazon Web Services (AWS) utilizing EC2 as of March 13, 2025.
Prerequisites
- AWS Account: With EC2 access.
- Hardware: g5.xlarge (NVIDIA A10G, 24GB VRAM).
Deployment Steps
Step 1: Launch EC2
AMI: Deep Learning AMI (Ubuntu 20.04).
Instance: g5.xlarge.
Storage: 50GB.
Step 2: Connect
SSH:
ssh -i <key.pem> ubuntu@<ec2-ip>
Step 3: Install and Download
Clone and download:
git clone https://github.com/Wan-Video/Wan2.1.gitcd Wan2.1huggingface-cli download Wan-AI/Wan2.1-T2V-14B --local-dir ./modelspip3 install -r requirements.txt
Step 4: Run Wan2.1
Generate video:
python3 inference.py --model_path ./models/Wan2.1-T2V-14B --prompt "A futuristic city" --output city.mp4
Requirements
- Instance: g5.xlarge
- VRAM: 24GB
- Cost/Hour: $1.006
Conclusion
As of March 2025, scalable video creation is made possible by deploying Wan 2.1 on AWS with a g5.xlarge instance. This configuration balances cost and performance for sophisticated AI video operations, making it ideal for companies and developers.
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AI/ML