What it is
ThinkDiffusion is a cloud-hosted workspace for running open-source generative model tools and model-training pipelines, with explicit support for Stable Diffusion, Hunyuan, Wan and related systems. The platform provisions private, dedicated virtual machines and persistent per-user storage so interfaces such as Automatic1111, ComfyUI, Fooocus, Forge and Kohya can be used in a hosted environment without local installation. It supports both image generation and model development workflows, including training and fine-tuning of models, LoRAs and textual inversions. ThinkDiffusion also publishes business-facing offerings: a commissionable AI art studio, training and consultancy, and education-oriented plans for schools, students and institutional teams. Workspaces are described as private and directly manageable from multiple devices.
Key features
The service exposes a range of features for working with community tooling and assets: selectable open-source UIs (Automatic1111, ComfyUI, Fooocus, Forge, Kohya), one-click machine launch, and the ability to run multiple or simultaneous machines. Users receive a dedicated GPU and a customizable persistent drive (up to 200GB as listed) for storing models, checkpoints, safetensors, embeddings and textual inversions. Uploads can be performed by drag-and-drop or one-click via URL from sources such as Civitai and Hugging Face. The environment permits installation of extensions and custom nodes, including Automatic1111 extensions and ComfyUI nodes, and Forge-specific features like IP Adapter masks and Flux support are available in that UI. The platform is accessible from any device and emphasizes private, single-user workspaces.
Use cases
ThinkDiffusion targets creators, technical users and organizations that need cloud-hosted access to open-source generative tools. Typical uses include producing AI-generated artwork through hosted UIs, training or fine-tuning models and LoRAs, and experimenting with node-based ComfyUI workflows for research or education. Agencies, brands and universities can commission studio work, run team-oriented projects, or provide students with classroom environments without local GPU setup. Developers and power users can install custom extensions, manage assets centrally, and scale work by launching multiple machines for parallel experimentation or production tasks.
