Ernie GGUF Switcher: Turbo-Charged Flux Efficiency

This workflow is designed for creators who demand high-fidelity results without the heavy hardware tax. By leveraging the Ernie-Image-Turbo model in GGUF format, this setup provides a streamlined, fast, and VRAM-efficient path to professional-grade AI imagery.

Key Features

GGUF Optimization: Optimized for lower VRAM usage via the UnetLoaderGGUF node, allowing high-end generation on mid-range hardware.

Turbo Performance: Uses the res_2s sampler with only 8 steps, delivering hyper-realistic results in a fraction of the time.

High-Resolution Ready: Defaulted to a 720x1024 portrait ratio, perfect for cinematic character shots and detailed textures.

Advanced CLIP Integration: Utilizes the ministral-3-3b CLIP model for superior prompt adherence and nuanced understanding of complex instructions.

Components & Nodes

Model: ernie-image-turbo-Q8_0.gguf

VAE: flux2-vae.safetensors

CLIP: ministral-3-3b.safetensors

Sampler: KSampler configured for speed (res_2s / simple scheduler).

How to Use

Ensure you have the ComfyUI-GGUF custom nodes installed.

Place your GGUF model in the models/unet folder and CLIP/VAE in their respective directories.

Input your prompt into the PrimitiveStringMultiline node and hit generate to see the "Turbo" efficiency in action.