HiDream-O1-Image-Dev-2604 — FP16 (ComfyUI)
This is the
FP16 conversion of
HiDream-ai/HiDream-O1-Image-Dev-2604 — the
updated distilled Dev variant of HiDream-O1-Image released May 13, 2026 — for use with
ComfyUI. This update brings accelerated IP inference, layout and skeleton conditioning support, and an updated editing scheduler. The Dev model runs in
28 steps at 9B parameters.
⚠️ PyTorch 2.9.x is not recommended — known compatibility issues exist. Use 2.8.x or earlier.
⚠️ Editing note: For instruction-based image editing tasks, the upstream team recommends using the full model instead of Dev.
What's New in Dev-2604
- Accelerated IP inference — faster subject-driven personalization
- Layout conditioning — place subjects at specific bounding box regions
- Skeleton conditioning — OpenPose-based pose control for try-on and character workflows
- Updated editing scheduler — improved Dev editing behaviour
Dev vs Full — Key Differences
| Full Model | Dev-2604 (this repo) |
|---|
| Parameters | 9B | 9B |
| Inference Steps | 50 | 28 |
| Guidance Scale (CFG) | 5.0 | 0.0 (disabled) |
| Shift | 3.0 | 1.0 |
| Scheduler | FlowUniPCMultistepScheduler | FlashFlowMatchEulerDiscreteScheduler |
| Speed | Slower, more detail | ~2× faster |
CFG is disabled in Dev mode — negative prompts have no effect.
BF16 vs FP16: Both use 16 bits per weight and have identical VRAM usage. BF16 has a wider dynamic range; FP16 has higher mantissa precision. Differences at inference are typically negligible. If you encounter NaN/Inf errors with FP16, switch to the BF16 variant.
VRAM Requirements
| Precision | Approximate VRAM |
|---|
| BF16 | 17 – 20 GB |
| FP16 (this repo) | 17 – 20 GB |
| FP8 Mixed | ~10 GB |
Quick Start — ComfyUI
1. Install the Custom Node
1cd ComfyUI/custom_nodes
2git clone https://github.com/Saganaki22/HiDream_O1-ComfyUI.git
3cd HiDream_O1-ComfyUI
4python -m pip install -r requirements.txt
Or search for HiDream O1 in ComfyUI Manager.
Suggested transformers version: 4.57.1 – 5.3 (newer versions may break compatibility).
2. Download the Weights
Download the entire model folder (all files, not just the safetensors) and place it in ComfyUI/models/diffusion_models/:
1huggingface-cli download drbaph/HiDream-O1-Image-Dev-2604-FP16 \
2 --local-dir ComfyUI/models/diffusion_models/HiDream-O1-Image-Dev-2604-fp16
The folder must contain the full Hugging Face support files alongside the weights:
config.json, chat_template.json, generation_config.json, preprocessor_config.json, tokenizer.json, tokenizer_config.json, vocab.json, merges.txt, model.safetensors
3. Load in ComfyUI
Use the workflow provided in the custom node repository. The loader will detect dev in the folder name and automatically apply Dev settings (28 steps, no CFG, Euler scheduler). Point the model loader to HiDream-O1-Image-Dev-2604-fp16.
About HiDream-O1-Image
HiDream-O1-Image is a natively unified image generative foundation model built on a Pixel-level Unified Transformer (UiT) — no external VAEs, no disjoint text encoders. It encodes raw pixels, text, and task-specific conditions in a single shared token space, supporting:
- Text-to-image generation up to 2,048 × 2,048
- Instruction-based image editing (full model recommended)
- Subject-driven personalization with layout and skeleton conditioning
- Long-text and multilingual text rendering
It debuted at #8 in the Artificial Analysis Text to Image Arena (2026-05-05).
Key Features
- 🧬 Pixel-Level Unified Transformer — end-to-end on raw pixels, no VAE, no disjoint text encoder
- 🎨 One Model, Many Tasks — T2I, editing, personalization, layout, skeleton, storyboard
- ⚡ 28-Step Distilled Dev — ~2× faster than the full model
- 🖼️ Native High Resolution — direct synthesis up to 2,048 × 2,048
- 🧍 Skeleton & Layout Conditioning — OpenPose control and bounding-box subject placement
All Model Variants
Full Model
Dev Model (original)
Dev-2604 Model (updated, this series)
License
The original HiDream-O1-Image model and code are released under the MIT License. This FP16 conversion inherits the same license.
Links
