vllm-omni/recipes/HiDream-ai/HiDream-O1-Image.md

HiDream-O1-Image

HiDream-O1 text-to-image generation through the shared offline example

Summary

• Vendor: HiDream.ai
• Model: HiDream-ai/HiDream-O1-Image
• Task: Text-to-image
• Mode: Offline inference
• Maintainer: Community

When to use this recipe

Use this recipe to generate native-resolution images with HiDream-O1 on one or two CUDA GPUs. The two-GPU command shards the Qwen3-VL attention and MLP weights, as well as the timestep and pixel projections.

References

• Upstream model: HiDream-ai/HiDream-O1-Image
• Related offline example: examples/offline_inference/text_to_image/text_to_image.py
• Related issue: vllm-project/vllm-omni#3479

Hardware Support

GPU

1x H100 80GB

Environment

• OS: Linux
• Python: Match the repository requirements for your checkout
• Driver / runtime: NVIDIA CUDA
• vLLM version: Match the repository requirements for your checkout
• vLLM-Omni version or commit: Use the commit you are deploying from

Command

python examples/offline_inference/text_to_image/text_to_image.py \
  --model HiDream-ai/HiDream-O1-Image \
  --prompt "A cat is sitting next to a sign that says 'HiDream-O1 vLLM-Omni'" \
  --height 2048 \
  --width 2048 \
  --num-inference-steps 50 \
  --guidance-scale 5.0 \
  --seed 42 \
  --output hidream_o1_output.png

Verification

python -c "from PIL import Image; im = Image.open('hidream_o1_output.png'); print(im.mode, im.size)"

Expected output:

RGB (2048, 2048)

Notes

• The pipeline supports BF16 text-to-image generation.
• Requested sizes are matched to the closest resolution supported by the checkpoint.

2x H100 80GB

Environment

• OS: Linux
• Python: Match the repository requirements for your checkout
• Driver / runtime: NVIDIA CUDA
• vLLM version: Match the repository requirements for your checkout
• vLLM-Omni version or commit: Use the commit you are deploying from

Command

python examples/offline_inference/text_to_image/text_to_image.py \
  --model HiDream-ai/HiDream-O1-Image \
  --tensor-parallel-size 2 \
  --prompt "A cat is sitting next to a sign that says 'HiDream-O1 vLLM-Omni'" \
  --height 2048 \
  --width 2048 \
  --num-inference-steps 50 \
  --guidance-scale 5.0 \
  --seed 42 \
  --output hidream_o1_tp2_output.png

Verification

python -c "from PIL import Image; im = Image.open('hidream_o1_tp2_output.png'); print(im.mode, im.size)"

Expected output:

RGB (2048, 2048)

Notes

• Tensor parallelism shards the attention, MLP, timestep, and pixel projection weights across both GPUs.
• Image editing and image-conditioned generation are not supported.