darkmaniac7/TokForge-RealVisXL-Lightning-GGUF

TokForge — RealVisXL V4.0 Lightning GGUF (SDXL Quality)

A single self-contained GGUF for stable-diffusion.cpp, packaging RealVisXL V4.0 Lightning (SDXL, photoreal, few-step Lightning). The UNet is q8_0, the VAE is kept at f16, both CLIP text encoders included — everything in one file.

This is the GPU "Quality" image tier for the TokForge Android app: native 1024px photoreal SDXL on certified high-memory Qualcomm/Adreno devices via the OpenCL F16-GEMM route. It is not a CPU default — SDXL is too heavy for phone CPU — it is the opt-in photoreal step-up above the DreamShaper fast route.

Files

File	Size	Precision	Contents
realvisxl-v40-lightning-q8_0.gguf	~4.2 GB	q8_0 UNet / f16 VAE	CLIP-L + OpenCLIP-bigG + Lightning UNet + SDXL VAE

Recommended render settings (SDXL Lightning, few-step)

sampler:      dpm++2m
scheduler:    discrete
steps:        6   (4 = fast floor, 8 = extra refinement)
cfg-scale:    1.5
resolution:   1024x1024 (SDXL native)
backend:      OpenCL on high-memory Adreno (GPU); SDXL CPU is not a supported tier

stable-diffusion.cpp CLI example

sd -M img_gen \
  -m realvisxl-v40-lightning-q8_0.gguf \
  -p "close-up portrait, natural skin texture, 85mm, RAW photo, photorealistic" \
  --sampling-method dpm++2m --steps 6 --cfg-scale 1.5 \
  -W 1024 -H 1024 -o out.png

Provenance & how this was built

1. Loaded SG161222/RealVisXL_V4.0_Lightning (SDXL diffusers, fp16). Lightning is a baked few-step distilled checkpoint (no LoRA to fuse).
2. Exported to a single original-format SDXL .safetensors.
3. Converted to GGUF with stable-diffusion.cpp (-M convert --type q8_0, keeping the VAE at f16 via --tensor-type-rules '^first_stage_model\.=f16').

License & attribution

• License: openrail++ (inherited from RealVisXL V4.0 Lightning / SDXL).
• Base model: RealVisXL V4.0 Lightning by SG161222 — https://huggingface.co/SG161222/RealVisXL_V4.0_Lightning
• Built on top of Stable Diffusion XL (Stability AI).

The original openrail++ terms and attribution requirements propagate to this GGUF and any images generated with it.