PRX Pixel

PRXPixel is a pixel-space text-to-image generation model by Photoroom. A ~7B [PRXTransformer2DModel] denoises raw RGB images directly — no VAE is needed. The model is conditioned on a Qwen3-VL text encoder and uses flow matching where the transformer predicts the clean image at each step (x-prediction). The generation resolution is fed into the timestep modulation so the model is aware of the target size.

Available models

Loading the pipeline

[PRXPixelPipeline] requires transformers >= 4.57 (the version that introduced Qwen3VLTextModel). Load it with [~DiffusionPipeline.from_pretrained]:

import torch
from diffusers import PRXPixelPipeline

pipe = PRXPixelPipeline.from_pretrained("Photoroom/prxpixel-t2i", torch_dtype=torch.bfloat16)
pipe.to("cuda")

prompt = "A front-facing portrait of a lion in the golden savanna at sunset."
image = pipe(prompt, num_inference_steps=28, guidance_scale=5.0).images[0]
image.save("prxpixel_output.png")

Memory Optimization

For memory-constrained environments:

import torch
from diffusers import PRXPixelPipeline

pipe = PRXPixelPipeline.from_pretrained("Photoroom/prxpixel-t2i", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload()

# Or use sequential CPU offload for even lower memory
pipe.enable_sequential_cpu_offload()

PRXPixelPipeline

[[autodoc]] PRXPixelPipeline

• all
• call

PRXPipelineOutput

[[autodoc]] pipelines.prx.pipeline_output.PRXPipelineOutput