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latentdivergence/sd15-npu-8gen2
sd15-npu-8gen2 is a text-to-image model from latentdivergence. Use it when you need an image from a text prompt. The card lists the license as creativeml-openrail-m.
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).
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Updated Jul 14, 2026
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From the Hugging Face model README
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).
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 |
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.
Derived from Stable Diffusion 1.5 (CreativeML OpenRAIL-M); the Attachment A use-restrictions travel with these weights. Compiled with Qualcomm AI Hub.