| name | flux-txt2img |
| description | Build Flux txt2img workflows — Flux.1 Dev (SRPO), Flux 2 Klein 9B, Turbo LoRAs, FluxGuidance, and DualCLIPLoader patterns |
| globs | ["**/*.json"] |
Flux Text-to-Image Workflows
Overview
Flux is a guidance-distilled diffusion model family from Black Forest Labs. It uses a separate FluxGuidance node instead of KSampler CFG (which must always be 1.0). Three variants are available locally:
- Flux.1 Dev SRPO — Fine-tuned Flux.1 Dev with SRPO alignment. Uses DualCLIPLoader (T5XXL + CLIP-L). BF16 only.
- Flux 2 Klein 9B — Distilled Flux 2 variant. Uses single CLIPLoader (Qwen3-8B) +
flux2-vae.safetensors. Fast 4-step generation.
- Flux 2 Turbo LoRA — Applied to Flux.1 Dev for 4-step generation.
Models
Flux.1 Dev SRPO
| Component | Node | Model | Notes |
|---|
| UNET | UNETLoader | flux.1-dev-SRPO-BFL-bf16.safetensors | 22.7GB, BF16 only — FP8 produces broken results |
| CLIP | DualCLIPLoader (type=flux) | clip_name1: t5xxl_fp8_e4m3fn.safetensors, clip_name2: clip_l.safetensors | T5XXL (4.7GB) + CLIP-L (235MB) |
| VAE | VAELoader | ae.safetensors | Standard Flux/Z-Image VAE (320MB) |
Flux 2 Klein 9B
| Component | Node | Model | Notes |
|---|
| UNET | UNETLoader | bigLove_klein1.safetensors | 17.3GB, Klein 9B variant |
| CLIP | CLIPLoader (type=flux) | qwen_3_8b_fp8mixed.safetensors | Qwen3-8B in text_encoders/ (8.3GB) |
| VAE | VAELoader | flux2-vae.safetensors | Flux 2 specific VAE (321MB) |
Klein 9B vs Flux.1 Dev: Klein uses Qwen3-8B text encoder (not T5XXL + CLIP-L). It has a different VAE (flux2-vae.safetensors). 9B distilled runs in 4 steps; 9B base needs ~50 steps at CFG 5.0. Fits in ~20GB VRAM with FP8.
Flux 2 Turbo LoRA (applied to Flux.1 Dev)
| Component | Node | Model | Notes |
|---|
| LoRA | LoraLoaderModelOnly | flux2-turbo-lora.safetensors | 2.6GB, strength 1.0 |
| Alt LoRA | LoraLoaderModelOnly | Flux2TurboComfyv2.safetensors | Community variant, same size |
Conditioning
CLIPTextEncodeFlux (Recommended for Flux.1 Dev)
Provides separate prompt fields for each text encoder:
{
"class_type": "CLIPTextEncodeFlux",
"inputs": {
"clip": ["<dual_clip>", 0],
"clip_l": "short prompt for CLIP-L",
"t5xxl": "detailed description for T5XXL",
"guidance": 3.5
}
}
clip_l captures key semantic features. t5xxl expands and refines descriptions. For simple use, put the same prompt in both fields. Guidance is built into this node — no separate FluxGuidance needed.
FluxGuidance (Alternative)
If using standard CLIPTextEncode instead of CLIPTextEncodeFlux, apply guidance separately:
{
"class_type": "FluxGuidance",
"inputs": {
"conditioning": ["<clip_text_encode>", 0],
"guidance": 3.5
}
}
Guidance Values
| Scenario | Guidance | Notes |
|---|
| Short prompts | 3.5–4.0 | Tighter prompt adherence |
| Long/complex prompts | 1.0–1.5 | More creative freedom |
| Realism | 2.5 | Less glossy skin, richer detail |
| Standard | 3.5 | Default for most use cases |
Negative Conditioning
Flux does NOT support traditional negative prompts (guidance-distilled, CFG=1.0). Use ConditioningZeroOut:
{
"class_type": "ConditioningZeroOut",
"inputs": { "conditioning": ["<positive_cond>", 0] }
}
Or simply use an empty CLIPTextEncode for the negative input.
Sampler Settings
Flux.1 Dev SRPO
| Parameter | Standard | Notes |
|---|
| steps | 20 | Range: 20–28 |
| cfg | 1.0 | Always 1.0 — guidance is via FluxGuidance |
| sampler_name | ipndm | Author-recommended for SRPO |
| scheduler | beta | Author-recommended for SRPO |
| guidance | 3.5 | Via CLIPTextEncodeFlux or FluxGuidance |
| denoise | 1.0 | |
SRPO note: The ipndm/beta combo is specifically recommended by the SRPO author. Standard Flux settings (euler/simple) also work but ipndm/beta gives better results with this fine-tune.
Flux 2 Klein 9B (Distilled)
| Parameter | Value | Notes |
|---|
| steps | 4 | Distilled model, 4 steps is optimal |
| cfg | 1.0 | Always 1.0 |
| sampler_name | euler | |
| scheduler | simple | |
| denoise | 1.0 | |
Flux 2 Klein 9B (Base/Undistilled)
| Parameter | Value | Notes |
|---|
| steps | 50 | Full quality |
| cfg | 5.0 | Higher CFG for base model |
| sampler_name | euler | |
| scheduler | simple | |
Flux.1 Dev + Turbo LoRA
| Parameter | Value | Notes |
|---|
| steps | 4 | Turbo-distilled |
| cfg | 1.0 | |
| sampler_name | euler | |
| scheduler | simple | |
| lora_strength | 1.0 | |
Resolutions
| Aspect | Resolution | Megapixels |
|---|
| Square | 1024x1024 | 1.0MP |
| Portrait 3:4 | 896x1152 | 1.0MP |
| Landscape 4:3 | 1152x896 | 1.0MP |
| Landscape 16:9 | 1344x768 | 1.0MP |
| Portrait 9:16 | 768x1344 | 1.0MP |
Flux operates at ~1 megapixel natively. Dimensions should be multiples of 8.
Prompt Style
Natural language descriptions. No quality tags needed (unlike SDXL/Illustrious). Detailed, descriptive prompts work best.
Good: "A young woman with auburn hair sits at a sunlit cafe in Paris, wearing a cream linen blazer, soft bokeh background, shot on Sony A7III 85mm f/1.4"
Bad: "masterpiece, best quality, 1girl, cafe, paris"
Complete Workflow: Flux.1 Dev SRPO
{
"1": { "class_type": "UNETLoader", "inputs": { "unet_name": "flux.1-dev-SRPO-BFL-bf16.safetensors", "weight_dtype": "default" }},
"2": { "class_type": "DualCLIPLoader", "inputs": { "clip_name1": "t5xxl_fp8_e4m3fn.safetensors", "clip_name2": "clip_l.safetensors", "type": "flux" }},
"3": { "class_type": "VAELoader", "inputs": { "vae_name": "ae.safetensors"
Complete Workflow: Flux 2 Klein 9B (Distilled, 4-Step)
{
"1": { "class_type": "UNETLoader", "inputs": { "unet_name": "bigLove_klein1.safetensors", "weight_dtype": "default" }},
"2": { "class_type": "CLIPLoader", "inputs": { "clip_name": "qwen_3_8b_fp8mixed.safetensors", "type": "flux" }},
"3": { "class_type": "VAELoader", "inputs": { "vae_name": "flux2-vae.safetensors" }},
"4"
Klein note: Uses single CLIPLoader (not DualCLIPLoader) with type: "flux" and the Qwen3-8B text encoder from text_encoders/. The CLIP loader path resolves from models/text_encoders/.
Complete Workflow: Flux.1 Dev + Turbo LoRA (4-Step)
{
"1": { "class_type": "UNETLoader", "inputs": { "unet_name": "flux.1-dev-SRPO-BFL-bf16.safetensors", "weight_dtype": "default" }},
"2": { "class_type": "LoraLoaderModelOnly", "inputs": { "model": ["1", 0], "lora_name": "flux2-turbo-lora.safetensors", "strength_model": 1.0 }},
"3": { "class_type": "DualCLIPLoader", "inputs":
LoRA Support
Custom LoRAs (jellyfish, etc.)
Apply Flux LoRAs with LoraLoaderModelOnly between UNET and KSampler:
{
"class_type": "LoraLoaderModelOnly",
"inputs": {
"model": ["<unet_or_previous_lora>", 0],
"lora_name": "<lora_file>.safetensors",
"strength_model": 1.0
}
}
Klein LoRAs
Klein 9B LoRAs go in loras/Flux.2 Klein 9B/ subfolder:
klein_slider_detail.safetensors — Detail slider LoRA
VRAM Considerations
| Model | VRAM | Notes |
|---|
| SRPO BF16 + DualCLIP | ~24GB | Fills RTX 4090 exactly. Must use BF16 — FP8 is broken for SRPO |
| Klein 9B FP8 + Qwen3-8B | ~20GB | Fits comfortably on 4090 |
| SRPO + Turbo LoRA | ~24GB | Same as SRPO base |
- Always
clear_vram before switching to Flux from another model family
- T5XXL is the main VRAM consumer alongside the UNET — both stay loaded during sampling
- CLIP-L is small (235MB) and negligible
Tips
- KSampler CFG must always be 1.0 — all guidance is through
CLIPTextEncodeFlux or FluxGuidance
- SRPO requires BF16 — the FP8 quantization is known to produce broken results with this fine-tune
- For short prompts (1-2 sentences), increase guidance to 3.5–4.0. For long prompts (paragraph), decrease to 1.0–1.5
- Flux generates excellent text in images — put text to render in quotes within your prompt
- Klein 9B is the fastest option at 4 steps — use it for rapid iteration, then switch to SRPO for final quality
