This is the
BF16
conversion of
HiDream-O1-Image
for use with
ComfyUI
. Weights have been cast to
bfloat16
for a balance of precision and memory efficiency.
A GPU with at least
20 GB VRAM
is recommended for comfortable use at full 2048 × 2048 resolution. 24 GB cards (RTX 3090/4090, A5000, etc.) will have no issues.
Quick Start — ComfyUI
1. Install the Custom Node
cd ComfyUI/custom_nodes
git clone https://github.com/Saganaki22/HiDream_O1-ComfyUI
pip install -r HiDream_O1-ComfyUI/requirements.txt
Or install via
ComfyUI Manager
by searching for
HiDream O1
.
Open ComfyUI and use the workflow provided in the custom node repository. Point the model loader to
HiDream-O1-Image-bf16
.
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:
At only 9B parameters it matches or exceeds much larger open-source DiTs and leading closed-source models. 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, storyboard generation
🧠
Reasoning-Driven Prompt Agent
— built-in "thinking" agent that resolves layout and rendering before generation
🖼️
Native High Resolution
— direct synthesis up to 2,048 × 2,048
⚡
9B Parameters
— performance parity with models many times larger
GenEval
(compositional generation) — HiDream-O1-Image scores
0.90
overall at 9B params, second only to the 200B+ Pro variant and ahead of GPT Image 2 (0.89).
DPG-Bench
(dense prompt alignment) — Overall score
89.83
, ranking second behind the Pro variant.
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