license: creativeml-openrail-m
base_model: stable-diffusion-v1-5/stable-diffusion-v1-5
tags:
- stable-diffusion
- qnn
- hexagon
- npu
- snapdragon
- text-to-image
pipeline_tag: text-to-image
sd15-npu-8gen2
Stable Diffusion 1.5 compiled to Qualcomm Hexagon NPU context binaries for the Snapdragon 8 Gen 2, via Qualcomm AI Hub (w8a16: int8 weights, int16 activations).
Generates a 512x512 image in ~7 seconds fully on the NPU (no CPU fallback).
Chip-specific — read this
QNN context binaries are compiled per chip generation and will not load on another. Pick the build matching your Snapdragon:
| Repo | Chip | SoC | Hexagon |
|---|---|---|---|
sd15-npu-8elite |
Snapdragon 8 Elite | SM8750 | v79 |
sd15-npu-8gen3 |
Snapdragon 8 Gen 3 | SM8650 | v75 |
Layout
unet.onnx + unet_qairt_context.bin # EPContext wrapper + Hexagon binary
text_encoder.onnx + text_encoder_qairt_context.bin
vae.onnx + vae_qairt_context.bin
quant.txt # w8a16 scales, read at load
tokenizer/{vocab.json, merges.txt}
soc_model.txt, htp_arch.txt, kind.txt
The .onnx files are tiny EPContext wrappers carrying the quantize/dequantize nodes;
the weights live in the _qairt_context.bin Hexagon binaries. Load them with ONNX
Runtime's C++ API — the Java API cannot express the uint16 tensors these require.
quant.txt holds the w8a16 quantization scales, read at load rather than hardcoded,
so one engine can drive any chip's build.
License
Derived from Stable Diffusion 1.5 (CreativeML OpenRAIL-M); the Attachment A use-restrictions travel with these weights. Compiled with Qualcomm AI Hub.