Unlock Efficient Image Generation: A Comprehensive Workflow Guide
1. Workflow Overview

This workflow focuses on image generation comparison & optimization, featuring:
Dual-path Generation: Parallel outputs from Flux DiT and HiDream Sampler for side-by-side comparison.
Smart Prompting: Auto-generates prompts from input images via
BizyAirJoyCaption2
.VRAM Optimization: Integrated
PurgeVRAM
nodes for low-end GPUs.Output Fusion: Merges results into a comparison grid.
2. Core Models
Model Name | Function | Source |
---|---|---|
| Quantized Flux DiT for efficiency | Install via |
| T5 encoder (Flux-specific) | Manual download to |
| Fast standalone sampler | GitHub: |
3. Key Nodes
Node | Purpose | Installation |
---|---|---|
| Loads Flux DiT model | Requires |
| Rapid image generation | Manual GitHub install |
| Auto-generates image captions | Install |
| Stitches outputs for comparison | Via |
4. Workflow Groups
Group 1: Input & Prompting
Input: Uploaded image (e.g.,
c298b158...jpg
)Output: Generated prompt (e.g., "Pirate ship in a cosmic maelstrom")
Group 2: Dual-path Generation
Flux Path: Uses
Flux DiT
+T5 encoder
HiDream Path: Fast generation via
HiDreamSampler
Key param:
seed=114129529
(fixed for consistency)
Group 3: Output Fusion
ImageConcanate
merges images → Saves toComfyUI/output
5. Inputs & Outputs
Input Parameters:
Required:
Image file
,Resolution (default: 1024x1024)
Optional:
HiDream steps
,Flux quant strength (0.105)
Output:
Comparison grid image (saved as PNG)
6. Notes
Compatibility:
Flux DiT requires
nunchaku-fp16
config files.HiDream does not support dynamic resolution.
VRAM Management:
Enable
PurgeVRAM
if GPU <8GB to avoid crashes.
Optimization:
Flux's
svdq-int4
trades quality for speed—adjust as needed.