gguf-org/mageflow-gguf overview
mageflow gguf edit turbo <Gallery / run it with gguf diffusion bash gguf diffusion screenshot https://raw.githubusercontent.com/gguf org/gguf desktop/master/de…
Runs locally from ~329.7 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
Model README
---
license: mit
base_model:
- microsoft/Mage-Flow
widget:
- text: >-
change the cat to a dog
output:
url: dog.png
- text: >-
change the dog to a cat
output:
url: cat.png
- text: >-
add a headset to the sheep
output:
url: headset.png
---
mageflow-gguf
- edit-turbo
<Gallery />
run it with gguf-diffusion
gguf-diffusion
or run it with gguf-connector
ggc fu
benchmark (initial comparisons)
- inference (engine)
| |ggk (gk) |gguf-cpp/gguf-diffusion (ggml kernel) |stable-diffusion.cpp (full ggml)
|------------|-------------------|----------------|--------------------------|
|completed in |7-8s |24-25s |25-26s
|speed (base/complete) |3x |base (1x) |.95-1x
- replicate the results (benchmark table) above by:
ggk diffuser engine -- --diffusion-model mageflow-edit-turbo-nvfp4.gguf --vae pig_mageflow_vae_fp32-f16.gguf --llm qwen3vl-4b-it-q4_k_m.gguf --llm_vision mmproj-qwen3vl-4b-it-f16.gguf --ref-image sheep.png -p "a sheep in sunglasses" --cfg-scale 1.00 --steps 4 --sampling-method euler --diffusion-fa -v -o out.png
gguf-cpp diffuser engine -- --diffusion-model mageflow-edit-turbo-nvfp4.gguf --vae pig_mageflow_vae_fp32-f16.gguf --llm qwen3vl-4b-it-q4_k_m.gguf --llm_vision mmproj-qwen3vl-4b-it-f16.gguf --ref-image sheep.png -p "a sheep in sunglasses" --cfg-scale 1.00 --steps 4 --sampling-method euler --diffusion-fa -v -o out.png
./sd-cli --diffusion-model mageflow-edit-turbo-nvfp4.gguf --vae pig_mageflow_vae_fp32-f16.gguf --llm qwen3vl-4b-it-q4_k_m.gguf --llm_vision mmproj-qwen3vl-4b-it-f16.gguf --ref-image sheep.png -p "a sheep in sunglasses" --cfg-scale 1.00 --steps 4 --sampling-method euler --diffusion-fa -v -o out.pngRun gguf-org/mageflow-gguf with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models