license: openrail++
tags:
- stable-diffusion-xl
- realvisxl
- lightning
- qualcomm
- hexagon
- qnn
- npu
- text-to-image
- tokforge
library_name: qnn
pipeline_tag: text-to-image
inference: false
TokForge — RealVisXL V4.0 Lightning (Qualcomm Hexagon NPU)
RealVisXL V4.0 Lightning image generation for the Qualcomm Hexagon NPU (HTP), packaged for
on-device image generation in the TokForge Android app (dev.tokforge). This is the
higher-quality 1024×1024 "Faithful" tier alongside the SD1.5 NPU bundle.
vc410: this repo replaces the previous SDXL-Turbo bins (few-step distillation gave fused heads / doubled bodies / extra limbs) with RealVisXL V4.0 Lightning, which is adversarially distilled for deterministic few-step Euler and renders clean, photoreal people. The W8A16 NPU quant is unchanged — the checkpoint was the cure.
The model is quantized to W8A16 (8-bit weights, 16-bit activations) and compiled to QNN HTP context binaries that run on the phone's Hexagon DSP. The pipeline uses fp16 text encoders and a TAESDXL tiny-VAE decoder, runs 6-step EulerDiscrete, and is guidance-free (one UNet pass per step).
Based on
SG161222/RealVisXL_V4.0_Lightning —
CreativeML OpenRAIL++-M license (commercial use permitted, no revenue cap).
Format
QNN HTP context binaries (W8A16), native 1024px (128×128 latent). These are compiled for the
Hexagon DSP and are not a portable format like GGUF. The repo ships native sets for V73 / V75 /
V79 / V81; the app reads the device Hexagon arch (dsp_arch) and downloads the matching set.
Forward-compatibility (a lower-arch binary also runs on a higher-arch DSP) still applies as a
fallback. Device-verified clean on V75 (Lenovo SM8650) and V81 (RedMagic SM8850).
Pipeline
| Stage | File |
|---|---|
| CLIP-L text encoder (fp16) | <arch>/text_encoder_1_fp16.bin |
| OpenCLIP-bigG text encoder (fp16) | <arch>/text_encoder_2_fp16.bin |
| Combined-emb MLP (host CPU) | <arch>/sdxl_emb_mlp.bin |
| UNet (W8A16, DSP) | <arch>/unet.bin |
| TAESDXL tiny-VAE (CPU MNN) | <arch>/taesdxl_decoder.mnn |
| Dual CLIP BPE tokenizers | <arch>/tokenizer/, <arch>/tokenizer_2/ |
Scheduler: EulerDiscrete (deterministic), trailing spacing, epsilon prediction, 6 steps,
guidance_scale 0. Runs via the license-clean libsdxl_qnn_driver in the TokForge app.
See manifest.json for the per-arch file list, sizes, and md5 checksums.