Intro If you’ve been following along, we’ve already covered vLLM-Omni and how diffusion models work. But here’s the dirty secret of diffusion models: they don’t run a single expensive computation, they run it many times per generation. 50 steps means 50 full forward passes through a multi-billion-parameter transformer. That’s a lot of GPU hours burned …
Intro Today, most of us have used nano banana, Midjourney, Kling AI, Luma, or Sora to generate silly videos or catchy images on socials. But what do they share in common? They all rely on Diffusion Models as their core engine, even the brand new Seedance. While many of these are proprietary, the open-source world …
Read more “Diffusion Models explained: From Noise to Pixels”
Intro Any-to-any multimodal models combining text, images, video, and audio are advancing AI, but their complex architectures, mixing autoregressive LLMs and diffusion transformers, make efficient serving very difficult. Current systems like OpenAI’s ChatGPT (text) and Sora (video) run as separate engines, lacking unified any-to-any pipelines. vLLM-Omni solves just that with a fully disaggregated serving system …