Latent Consistency Model
A Latent Consistency Model (LCM) is a diffusion model distilled to generate high-quality images in 4-8 steps instead of the 50+ required by original models. Consistency distillation trains the model to map any noisy latent directly to the clean output in a single step, eliminating the iterative denoising process. LCM-LoRA applies this speedup to any existing Stable Diffusion model without requiring full distillation from scratch. The practical result is real-time image generation (~30 fps on a consumer GPU) and the ability to iterate visually on prompts interactively.
In practice
A developer can use LCM-LoRA with HuggingFace diffusers by adding a single adapter to their existing Stable Diffusion pipeline: download the LCM-LoRA weight, set the scheduler to LCMScheduler, and reduce num_inference_steps to 4. The quality is equivalent to 50 steps but 10x faster. For real-time generative UI applications (e.g., interactive sketch-to-image), this speed is essential; LCMs are often combined with StreamDiffusion to further optimize throughput.