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LatestBlack Forest Labs2-small-decoder
Black Forest LabsText → Image

Black Forest Labs Releases Open FLUX.2 Image Decoder

This new component is part of a novel transformer-based architecture for text-to-image generation, released under a permissive Apache 2.0 license.

Apr 6, 2026
NotableApache 2.0
FLUX.2 small decoder

Black Forest Labs has released a key component of its new image generation architecture, the FLUX.2 small decoder. Available under a permissive Apache 2.0 license, this decoder is designed for high-performance text-to-image and image editing tasks, signaling a new contender in the open-source creative AI space.

The release is significant not just for the tool itself, but for the underlying architecture it represents. Unlike established latent diffusion models like Stable Diffusion that rely on a U-Net, the FLUX architecture uses a transformer-based design. The goal is to process text and image information in a more unified, parallel manner, which could lead to improvements in speed and coherence.

This release contains only the "small" decoder model. As detailed in the official repository, the decoder is one part of a larger system that includes a main transformer for processing prompts and generating image latents. The full model suite, including a larger variant, has not yet been published, making this a component-first preview of the new technology.

By open-sourcing this foundational piece, Black Forest Labs is giving developers an early look at a different approach to image synthesis. The move away from U-Nets towards diffusion transformers mirrors trends in the field, and the arrival of FLUX.2 suggests the open-source ecosystem will soon have another powerful and distinct architecture to build upon.

Sources

  • black-forest-labs/FLUX.2-small-decoder

    Hugging Face

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OlderZhipu AI Releases Open-Source GLM-5.1 MoE ModelZhipu AI · Text / LLM · 7 months agoNewerBaidu Releases 8B Text-to-Image Model ERNIE-ImageBaidu · Text → Image · 7 months ago

Get the model

Hugging Face

Specs

Size200 MB
PrecisionFP32
LicenseAPACHE-2.0
Downloads174.3K
Likes187

Can you run it?

Runs on just about anything.

  • FP32 (as published)

    Any modern laptop · 8 GB RAM

    1.2 GB
  • 16-bit

    Any modern laptop · 8 GB RAM

    1.1 GB
  • FP8

    Any modern laptop · 8 GB RAM

    1.1 GB
Your machine
  • Covers the published checkpoint; text encoders and VAE loaded alongside may add a few GB (many runtimes offload them to CPU).

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Image EditingText → Image

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