SD WebUI Forge screenshot thumbnail

SD WebUI Forge

With 12,800 GitHub stars and backing from the same developer who created ControlNet, Stable Diffusion WebUI Forge replaces Automatic1111's inference backend with a dynamic GPU memory management system that runs SDXL 30-75% faster while consuming significantly less VRAM — enabling 1024x1024 generation on 6GB cards where A1111 requires 8GB or more. The Gradio 4 interface provides txt2img, img2img, inpainting, and outpainting workflows with a Forge Canvas supporting pressure-sensitive input from Wacom tablets and Microsoft Surface devices. Native Flux.1 model support loads Flux Dev and Schnell checkpoints using BitsandBytes NF4 and FP8 quantization for deployment on consumer GPUs without model splitting. Built-in ControlNet integration includes all preprocessors — Canny, Depth, Normal, OpenPose, MLSD, Scribble, Segmentation, Tile, and IP-Adapter — without requiring separate extension installation. The extension ecosystem maintains full compatibility with popular Automatic1111 extensions including Adetailer for face enhancement, After Detailer, Regional Prompter, and Dynamic Prompts. LoRA loading supports standard, LyCORIS, and DoRA formats with automatic weight detection. The API provides RESTful endpoints for txt2img, img2img, extra single/batch processing, and progress monitoring enabling headless batch generation. Deploy via one-click installer package, Python virtual environment, or Docker with NVIDIA GPU passthrough. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

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Infinite Canvas screenshot thumbnail

Infinite Canvas

Instead of juggling a chat window, a folder of reference images, and a notebook of half-remembered prompts, Infinite Canvas puts the whole image-making process on one zoomable board. Drop in text, image, video, and generation-settings nodes, then wire them together so every result stays connected to the prompt and references behind it. Add one or several OpenAI-compatible endpoints, choose default text, image, and video models, and set image count, aspect ratio, quality, and transparent backgrounds per node. Batch results arrive as linked nodes that remember their prompt, model, and dimensions, so any of them can be retried later with the same settings. A prompt library searches seven built-in sources plus your own JSON sources and inserts the winner straight onto the board. An asset shelf keeps reusable images, clips, and audio within reach. Projects can be duplicated, exported, and synced between devices over WebDAV. Want a helper? A local Canvas Agent lets Codex read the active board and edit it through MCP, with approvals and permissions shown in a side panel. Plugins add node types, inspectors, and toolbar actions. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

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