MossInt4

Small int4 versions of the Moss image model and its Qwen3.5 9B text encoder, made for running fully in the browser with WebGPU. Everything is kept small to fit the browser's limits: WebAssembly can address at most 4 GB, WebGPU buffers are capped at 2 GB, and most GPUs have 8-12 GB of VRAM. The files are streamed with HTTP range requests straight into GPU buffers and cached in the browser (OPFS), so they never have to fit into WebAssembly memory as a whole.

They are used by the StrictComfy browser page, which runs 100% locally on your device with WebGPU, written in Strict. The downloadable GitHub version (int8, CUDA) is up to 10x faster.

Files

File	Size	Content
moss_image_sft_4step_int4_convrot.safetensors	3.0 GB	Moss Image SFT with the 4-step LoRA merged, for 4 and 2 steps (fastest, fastest2steps)
moss_image_sft_dmd_int4_convrot.safetensors	3.0 GB	Moss Image SFT with the DMD turbo LoRA merged, for 8 steps (best, fast, faster)
qwen3.5_9b_int4_convrot.safetensors	4.5 GB	The language model of Qwen3.5 9B as the text encoder (no vision, MTP or output head)

Format

ComfyUI's convrot_w4a4 layout: every linear layer is rotated with a 256-wide Hadamard transform, stored as signed 4-bit codes (two per byte, I8) with one F32 scale per row, chosen by a clip search per row (mean relative row error 11.4 %). Norms and small tensors stay BF16/F32, the Qwen embedding stays int8. The LoRAs were merged into the bf16 weights before quantizing; the Qwen file was requantized from the int8 convrot release. Computation runs with 8-bit activations (WebGPU dot4I8Packed), so the int4 weights mainly save download size and memory.

Compared with the int8 originals the images keep the same composition with small differences in fine detail; the text encoder's context has a cosine similarity of 0.96 to int8.

License

Apache 2.0, like everything they are made from. These files are modified versions (LoRAs merged, quantized to int4) of:

• OpenMOSS-Team/MOSS-Image-SFT
• akhaliq/MOSS-Image-SFT-4-steps (4-step LoRA)
• lodestones/MOSS-Image-SFT-8-steps-dmd (DMD LoRA)
• Qwen/Qwen3.5-9B