Dreamlook

Dreamlook is a cloud-based platform specialized in fine-tuning Stable Diffusion models, particularly SDXL and SD1.5, with a strong emphasis on speed and scalability. The service allows users to train custom models — including full SDXL checkpoints, not just LoRA adapters — in as little as 10 minutes for 1,500 training steps, while maintaining output quality comparable to longer training runs. The platform is built to handle high-volume workloads, supporting up to thousands of training runs per day, making it suitable for teams or individuals who need to iterate rapidly on many different concepts or datasets. One of the core features is the ability to generate full-resolution SDXL images (typically 1024×1024) in about 4 seconds, leveraging optimized inference pipelines. This fast generation capability extends to both SD1.5 and SDXL models, enabling quick prototyping and batch production. For users who prefer lightweight model distribution, Dreamlook offers an option to extract LoRA files from full checkpoints, reducing the file size of downloaded artifacts without losing the fine-tuned behavior. This is particularly useful for sharing custom styles or characters across different applications or storage-constrained environments. The platform also provides a scalable fine-tuning API, designed to integrate into larger applications or workflows. By abstracting away GPU provisioning, instance management, and scaling logic, the API lets developers focus on their own product logic rather than infrastructure overhead. Users can start training with no upfront payment and no credit card required, lowering the barrier for experimentation. Training is billed per run, and the system automatically handles queuing and parallel execution across available GPUs. Dreamlook supports advance