Research Overview
This research collection explores different approaches to setting up self-hosted AI environments on AWS EC2 instances. These guides provide detailed instructions for deploying models like Llama 3, Mistral, DeepSeek, and others on cost-effective GPU instances, enabling powerful AI capabilities without recurring SaaS subscription fees.Research Collection
Gemini AI Setup
A comprehensive guide to building your own cloud AI development environment using AWS EC2, Ollama for running models, and Code-Server for a browser-based VS Code experience. Includes detailed cost-saving strategies and security setup.
View ResearchFlowith AI Deployment
Step-by-step guide for setting up a production-ready AI agent environment on AWS EC2 with clean interface. Features EC2 instance recommendations, deployment scripts, Nginx configuration, and automatic shutdown for cost optimization.
View ResearchDeepSeek AI Config
Focused deployment guide for implementing DeepSeek models on AWS EC2. Includes instance recommendations, auto-setup scripts, server configuration options, and comprehensive cost estimates with both GPU and CPU options.
View ResearchGrok AI Configuration
Tailored setup for AWS EC2 instances using g6.xlarge for cost-effective GPU performance. Leverages Ollama for model execution with Open WebUI and includes Code-Server for remote development with detailed cost management strategies.
View ResearchManus AI Implementation
Detailed implementation guide that includes a comprehensive setup guide, setup scripts, and extensive documentation for deploying AI agents on AWS EC2 with a focus on security and performance optimization.
View ResearchComparative Analysis
| Platform | Recommended Instance | Monthly Cost (8h/day) | Best For |
|---|---|---|---|
| Gemini | g5.xlarge | ~$86 (Spot) | Development environment with code-server integration |
| Flowith | g5.4xlarge | ~$262 | Production environment for larger models (up to 30B) |
| DeepSeek | g4dn.xlarge | ~$205 | Specialized DeepSeek coder models |
| Grok | g6.xlarge | ~$193-201 | Latest generation GPU performance (NVIDIA L4) |
| Manus | g4dn.xlarge or g5.xlarge | ~$75-205 | Comprehensive deployment with security focus |
Key Insights
All approaches demonstrate significant cost savings compared to subscription AI services, especially when implementing auto-shutdown features during idle periods. Using spot instances can further reduce costs by 60-70%. The g4dn.xlarge offers good value for smaller models, while g5.xlarge/g5.4xlarge provide better performance for larger models or higher throughput requirements.
Best Practices
Implementing Nginx with SSL certificates ensures secure access, while auto-shutdown scripts during off-hours minimize costs. Docker containerization simplifies deployment and maintenance across different server configurations.
Looking for Other Resources?
Check out my other technical guides and documentation: