NEWS · CODING · #1149
Generate images and image-conditioned video on SageMaker AI using AWS vLLM-Omni DLC (FLUX.2-klein-4B → Wan2.1-VACE-1.3B)
An AWS blog post demonstrates deploying the same AWS vLLM-Omni Deep Learning Container to two SageMaker AI endpoints: a real-time endpoint running FLUX.2-klein-4B for image generation and an asynchronous endpoint running Wan2.1-VACE-1.3B for image-conditioned video generation. The sample workflow generates a PNG from text, passes it (via S3) to the video endpoint, retrieves the MP4 from S3, and includes CLI and optional Streamlit examples.
KEY POINTS
- An AWS blog post demonstrates deploying the same AWS vLLM-Omni Deep Learning Container to two SageMaker AI endpoints: a real-time endpoint running FLUX.2-klein-4B for image generation and an asynchronous endpoint running Wan2.1-VACE-1.3B for image-conditioned video generation.
- The sample workflow generates a PNG from text, passes it (via S3) to the video endpoint, retrieves the MP4 from S3, and includes CLI and optional Streamlit examples.
- It provides a practical pattern for running multimodal workloads on SageMaker AI—reusing one vLLM-Omni DLC image while routing real-time and long-running inference to appropriately configured endpoints and S3-backed async I/O.
WHY IT MATTERS
It provides a practical pattern for running multimodal workloads on SageMaker AI—reusing one vLLM-Omni DLC image while routing real-time and long-running inference to appropriately configured endpoints and S3-backed async I/O.