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How to generate images and video with SGLang Diffusion with SGLang

Use the diffusion engine built into the same package to serve image and video models.

Short answer: Install SGLang (the diffusion engine is included in the Python package); then follow the SGLang Diffusion installation guide; launch a diffusion model and send a generation request. All steps.

Who it is forA team that already serves LLMs with SGLang and wants image or video generation on the same stack.

The problemRunning a separate stack for diffusion models doubles the ops work.

The outcomeImage or video generation served from the SGLang package you already run.

What you need first

  • A supported GPU or accelerator (NVIDIA, AMD, TPU and others)
  • Docker, or a Python environment with uv

Steps

  1. Install SGLang (the diffusion engine is included in the Python package)
  2. Follow the SGLang Diffusion installation guide
  3. Launch a diffusion model and send a generation request

Prompt for your agent

Using sgl-project/sglang's built-in SGLang Diffusion, serve <diffusion model> on this GPU and generate one test image from <prompt>. Report memory use and time per image.

Caveat.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for sgl-project/sglang and "Generate images and video with SGLang Diffusion"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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