FLUX.2 [klein] 4B + Qwen3-4B — quantized WebGPU bundles
Quantized, browser-streamable repacks of
FLUX.2 [klein] 4B
(rectified-flow image transformer + VAE) and
Qwen3-4B
(as the text encoder — hidden-state taps at layers 9/18/27), packed
for fully client-side WebGPU inference: no server-side compute,
weights fetched with plain HTTP GETs and streamed straight into GPU
buffers.
| bundle | contents | size | quantization |
|---|
flux2-q8/ | FLUX.2 klein transformer + VAE | ~4.0 GB | int8 g64 matmuls, f16 rest |
qwen3-q8/ | Qwen3-4B layers 0–26 + tokenizer | ~3.2 GB | int8 g64 |
qwen3-q4/ | Qwen3-4B layers 0–26 + tokenizer | ~1.85 GB | int4 g64, int8 embeddings |
gdino-q8/ | Grounding DINO base (full detector) | ~328 MB | int8 g64, Swin at f16 |
sam2-q8/ | SAM 2.1 hiera-small (image path) | ~41 MB | int8 g64 |
The bundle layout is purpose-built for streaming into WebGPU (not a
standard interchange format like safetensors or GGUF): each bundle
directory holds a manifest.json (tensor table, shard offsets,
tokenizer/chat-template segments) plus shard_NNN.bin files (~250 MB
each) — CDN/CORS friendly, cacheable as immutable content.
Quality
Validated end-to-end against the original-weights reference
implementation (fp32 eager) on identical inputs:
- transformer velocity field: cosine ≥ 0.9998
- VAE decode: cosine ≥ 0.99999; VAE encode: cosine ≈ 1.0
- Qwen3 hidden-state taps (q4): cosine ≥ 0.998 at all three taps
- tokenizer: exact match on multilingual/emoji probe set
- Grounding DINO: reference detections reproduced end-to-end (IoU >
0.9, scores within ±0.03, labels exact) vs fp32 eager
- SAM 2.1: reference masks reproduced at IoU 0.998+ with matching
predicted-IoU scores
An int4 variant of the image transformer failed these gates
(velocity cosine 0.96) and is deliberately not published.
Runtime requirements
A consuming runtime needs WebGPU with ~8 GB of GPU/unified memory for
flux2-q8 + qwen3-q4; shader-f16 is used when available. Validated on
Chrome (Vulkan, D3D12, and Metal backends) and Safari 26+.
Character-reference conditioning (multi-image) is supported natively
by the packed transformer weights.
License and attribution
Both source models are licensed under the
Apache License 2.0; these repacks are derivative works
distributed under the same license. See
NOTICE for
required attributions and the full statement of modifications
(quantization parameters, omitted layers, format changes).
Not affiliated with or endorsed by Black Forest Labs Inc., Alibaba
Cloud, IDEA-Research, or Meta Platforms. "FLUX" is a trademark of Black Forest Labs Inc., used here only
to describe the origin of the weights.
