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license: apache-2.0
language:
- en
pipeline_tag: image-to-image
tags:
- text-to-image
- image-editing
- flux
- diffusion-single-file
base_model:
- black-forest-labs/FLUX.2-small-decoder
base_model_relation: quantized
---
This is a BF16 conversion of [`black-forest-labs/FLUX.2-small-decoder`](https://huggingface.co/black-forest-labs/FLUX.2-small-decoder), converted using `diffusers` and `safetensors`. Weights cast from FP32 to BF16; `bn` statistics preserved as-is.
`FLUX.2 Small Decoder` is a distilled VAE decoder that serves as a **drop-in replacement** for the standard FLUX.2 decoder. It delivers faster decoding and lower VRAM usage with minimal to zero quality loss. The encoder remains unchanged.
Both images below have been generated using FLUX.2 Klein NVFP4 with BF16 VAEs.
<table style="width:auto">
<tr>
<td align="center"><a href="./images/flux2-vae-small.png"><img src="./images/flux2-vae-small.png" style="width:65%"/></a></td>
<td align="center"><a href="./images/flux2-vae-small.png"><img src="./images/flux2-vae.png" style="width:65%"/></a></td>
</tr>
<tr>
<td align="center"><b>FLUX.2 VAE small</b></td>
<td align="center"><b>FLUX.2 VAE</b></td>
</tr>
</table>
**Prompt**
<pre>A black cat holding a sign that says 'hello world' in typewriter font</pre>
# **Key Features**
1. **~1.4x faster decoding** compared to the full decoder.
2. **~1.4x less VRAM** at decode time, enabling higher resolutions without running out of memory.
3. **~28M decoder parameters** (vs ~50M in the full decoder) thanks to narrower channel widths (`[96, 192, 384, 384]` vs `[128, 256, 512, 512]`).
4. **Minimal quality loss** — images are almost identical.
5. Available under the Apache 2.0 license.
Compatible with all open FLUX.2 models:
- [FLUX.2-klein-4B](https://huggingface.co/black-forest-labs/FLUX.2-klein-4B)
- [FLUX.2-klein-9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-9B)
- [FLUX.2-klein-9b-kv](https://huggingface.co/black-forest-labs/FLUX.2-klein-9b-kv)
- [FLUX.2-dev](https://huggingface.co/black-forest-labs/FLUX.2-dev)
---
# License
This model is licensed under the https://www.apache.org/licenses/LICENSE-2.0. |