1. Workflow Overview

This workflow specializes in generating Eastern-style illustrations using Flux technology stack. Key features:

• Dual CLIP encoders (t5xxl_fp8 + clip_l)

• High-res output (2272x1280)

• Style enhancement via Lora

Core Models:

• BaseAlgo_F.1: Main model (FP8 optimized)

• ae.sft: Dedicated VAE

• FantasyMirage.lora: Style adapter (0.9 strength)

2. Node Breakdown

Critical Nodes:

1. DualCLIPLoader

   • Loads t5xxl_fp8_e4m3fn (Chinese-optimized) + clip_l

2. FluxGuidance

   • Advanced conditioning control (CFG=3.5)

3. GetNode/SetNode

   • Data routing system:

     • "1": Latent flow

     • "c": CLIP model flow

     • "l": Conditioning flow

4. easy cleanGpuUsed

   • VRAM cleaner (requires KJNodes)

Dependencies:

• FP8 support (RTX 30/40 series)

• ComfyUI-Flux recommended

3. Workflow Structure

Generation Stages:

1. Text Encoding

   • Processes complex Chinese prompts (e.g. philosophical descriptions)

2. Latent Generation

   • Euler sampler (20 steps)

   • Empty latent: 2272x1280 (batch=4)

3. Post-Processing

   • Auto VRAM cleanup

   • Dual output channels

4. I/O Specification

Inputs:

• Positive prompt:

  Cascading ochre-yellow composition...(200+ words artistic description)  

• Seed: 566815113879132 (randomizable)

Outputs:

• Path: /ComfyUI/

• Format: PNG (ultra-high res)

5. Critical Notes

1. Hardware

   • FP8 support required

   • VRAM: ≥16GB (for 2272px)

2. Model Paths

   • Main model: ComfyUI/models/unet/

   • Loras: ComfyUI/models/loras/

3. Troubleshooting

   • NaN errors: Reduce FluxGuidance CFG

   • VRAM issues:

     Decrease batch size in EmptyLatentImage (current:4)