Building a Free AI Image Generator on 7 GPUs: Architecture Deep Dive
Most tutorials about running AI inference at scale assume you have access to cloud GPU clusters, Kubernetes, and a team of infrastructure engineers. I had none of that. What I had was a single work...

Source: DEV Community
Most tutorials about running AI inference at scale assume you have access to cloud GPU clusters, Kubernetes, and a team of infrastructure engineers. I had none of that. What I had was a single workstation with 7 NVIDIA RTX 5090 GPUs, a fiber internet connection, and a goal: serve free AI image generation to anyone on the internet without a signup wall. This is the architecture that makes ZSky AI work. Every design decision here came from a real production failure or bottleneck, not from a whiteboard exercise. The Constraints That Shaped Everything Before diving into the architecture, here are the constraints that ruled out most "standard" approaches: Single machine. All 7 GPUs live in one box. No cluster networking, no distributed training frameworks. Consumer hardware. RTX 5090s, not A100s or H100s. Consumer drivers, consumer cooling, consumer power delivery. Real-time serving. Users expect results in under 4 seconds. Batch processing is not an option. Mixed workloads. Image generatio