Iris-3B

Pixel-space generation & general vision learner

Iris-3B is a pixel-space generative model that can act as a general vision learner. Working in pixel space, it bypasses the lossy compression and the biased, texture-focused latents of a VAE. We show image generators can replace vision models such as DINOv2, release our pixel-space scaling recipes, and put the generative prior to work on dense tasks where detail matters.

arXiv Code Weights Spaces

Hanqiu Li Cai^†Chema GarabitoSperidlabs · † project lead

02 — Gallery

Gallery

03 — Architecture

Architecture

A 3B flow-matching transformer that generates raw RGB pixels directly, with no VAE in the loop.

FIG. 02 — ArchitectureTrunk · PiT head · trunk block

Images are cut into 16 × 16 pixel patches. The trunk has 8 dual-stream blocks, with separate text and image weights, followed by 16 single-stream blocks.

A small pixel-transformer (PiT) head decodes each patch token back to pixels. Text comes from a frozen Qwen3-VL-4B encoder, and 2D RoPE lets one set of weights run at any resolution and aspect ratio up to one megapixel.

04 — Benchmarks

Benchmarks

Competitive with state-of-the-art latent models on every official benchmark, at a fraction of their training compute.

Model	GenEval	DPG	LongText	OneIG
SDXL	—	74.65	—	0.316
SD3 Medium	0.62	84.08	—	—
FLUX.1-dev 12B	0.66	83.8	0.607	0.434
SD3.5 Large	0.71	—	—	0.462
Lumina-Image 2.0	0.73	87.20	—	0.353
Janus-Pro-7B	0.80	84.19	0.019	0.267
HiDream-I1-Full	0.83	85.89	0.543	0.477
Z-Image 6B*	0.84	88.1	0.935	0.546
Qwen-Image 20B	0.87	88.3	0.943	0.539
Iris-3B	0.798	86.52	0.857	0.540

Iris-3B: official evaluators at 1024², no prompt rewriting, no best-of-N. References from the Qwen-Image and Z-Image reports; — not reported; * uses prompt rewriting.

05 — Downstream

Downstream

Iris-3B tuned for downstream tasks.

05.A

Depth

PhotoDepth

PhotoDepth

PhotoDepth

PhotoDepth

PhotoDepth

PhotoDepth

Point clouds from predicted depth · drag to orbit, scroll to zoom

05.B

Image Restoration / Super-resolution

InputIris-3B

06 — Citation

Cite this work

@techreport{licai2026iris,
  title       = {Iris-3B: Going Beyond the Latent with Pixel-Space
                 Diffusion Training, Conversion and Fine-Tuning},
  author      = {Li Cai, Hanqiu and Garabito, Chema},
  institution = {Speridlabs},
  year        = {2026}
}