#106
C
Rank #241
ComfyUI
A node-graph based UI for building and running Stable Diffusion and other image/video generation pipelines visually. Standout trait is its highly composable workflow-as-graph model, which power users export and share as JSON.
40.3
/ 100
⚙ Full Stack
Python backend built on PyTorch that executes a directed graph of nodes (checkpoints, samplers, VAEs) against CUDA-accelerated models; the web UI is a JS/Litegraph canvas talking to the backend over a local HTTP/WebSocket API. No database — workflows and outputs are just files on disk.
📈 Scaling Analysis
Fundamentally single-user, single-GPU by design — there's no job queue, multi-tenant isolation, or horizontal worker pool, so 'scaling' means running multiple independent GPU pods rather than one system scaling out. GPU cost and availability, not software architecture, is the real bottleneck.
🚀 Running on Nexlayer
Needs a GPU-backed pod (nvcr.io base image, not mirror.gcr.io, since CUDA images aren't Docker Hub official) and a persistent volume mounted for the multi-gigabyte `models/` directory. There is no built-in auth, so it must sit behind a Nexlayer-managed auth proxy pod rather than being exposed directly at `<% URL %>`.