ComfyUI-Flux2Klein-Enhancer

Conditioning enhancement node for FLUX.2 Klein 9B in ComfyUI. Built from empirical analysis of the model's conditioning structure.

What This Does

FLUX.2 Klein uses a Qwen3 8B text encoder that outputs conditioning tensors of shape [batch, 512, 12288]. Through diagnostic analysis, I found:

• Positions 0-77: Active text embeddings (std ~40.7)
• Positions 77-511: Padding/inactive tokens (std ~2.3)
• Image edit mode: Adds reference_latents to metadata

This node modifies only the active text region (0-77) to affect prompt adherence and edit behavior. The padding region is left untouched.

Installation

1. Navigate to your ComfyUI custom nodes folder:

   cd ComfyUI/custom_nodes/
   

2. Clone this repository:

   git clone https://github.com/capitan01R/ComfyUI-Flux2Klein-Enhancer.git
   

3. Restart ComfyUI

Nodes

FLUX.2 Klein Enhancer

General-purpose conditioning enhancement for both text-to-image and image editing workflows.

Parameters

Parameter	Default	Range	Description
text_enhance	0.0	-1.0 to 2.0	Scales magnitude of active tokens. Positive values increase prompt influence, negative values decrease it.
detail_sharpen	0.0	-1.0 to 2.0	Amplifies differences between tokens. Positive sharpens, negative smooths.
coherence_experimental	0.0	0.0 to 1.0	Self-attention pass across tokens. Experimental - start with low values (0.1-0.2).
edit_text_weight	1.0	0.0 to 3.0	Image edit mode only. Values below 1.0 preserve more of the original image, above 1.0 follows the prompt more strongly.
edit_blend_mode	none	none/boost_text/preserve_image/balanced	Image edit mode only. Preset configurations for common edit scenarios.
active_token_end	77	1 to 512	End position of active text region. Default based on diagnostic findings.
seed	0	0 to 2147483647	Random seed for reproducibility. 0 disables seeding.
debug	False	True/False	Prints tensor statistics and modification details to console.

FLUX.2 Klein Edit Controller

Fine-grained control specifically for image editing workflows.

Parameters

Parameter	Default	Range	Description
prompt_strength	1.0	0.0 to 3.0	Global multiplier for text conditioning influence.
preserve_structure	0.0	0.0 to 1.0	Applies smoothing to conditioning for more conservative edits.
token_emphasis_start	0	0 to 76	Start position of token range to emphasize.
token_emphasis_end	77	1 to 77	End position of token range to emphasize.
emphasis_strength	1.0	0.0 to 3.0	Multiplier for the emphasized token range.
debug	False	True/False	Prints debug information to console.

How It Works

Text Enhancement

The text_enhance parameter scales the magnitude of embedding vectors in the active region:

scale = 1.0 + (text_enhance * 0.5)
region = region * scale

A value of 0.5 results in a 1.25x magnitude increase. This affects how strongly the text conditioning influences the diffusion process.

Detail Sharpening

Computes the mean embedding across the sequence, then amplifies deviations from that mean:

seq_mean = region.mean(dim=1)
detail = region - seq_mean
sharpened = seq_mean + detail * (1.0 + sharpen)

This increases the distinctiveness of individual token embeddings.

Coherence (Experimental)

Projects embeddings to a lower dimension (1024), applies self-attention with temperature scaling, then projects back. This encourages tokens to share information but can cause artifacts at high values.

Image Edit Mode Detection

The node automatically detects image edit mode by checking for reference_latents in the conditioning metadata. When detected, edit_text_weight and edit_blend_mode become active.

Usage Examples

Text-to-Image: Stronger Prompt Adherence

text_enhance: 0.3
detail_sharpen: 0.2
coherence_experimental: 0.0
edit_text_weight: 1.0
edit_blend_mode: none

Image Edit: Follow Prompt More

text_enhance: 0.2
detail_sharpen: 0.1
coherence_experimental: 0.0
edit_text_weight: 1.5
edit_blend_mode: none

Image Edit: Preserve Original More

text_enhance: 0.0
detail_sharpen: 0.0
coherence_experimental: 0.0
edit_text_weight: 0.5
edit_blend_mode: none

Image Edit: My preferred settings:

text_enhance: 1.5
detail_sharpen: 0.0
coherence_experimental: 0.0
edit_text_weight: 2.0
edit_blend_mode: none

Debugging

Enable debug: True to see console output:

=== Flux2KleinEnhancer Item 0 ===
Input shape: torch.Size([1, 512, 12288])
Metadata keys: ['pooled_output', 'attention_mask', 'reference_latents']
Active region: 0 to 71
Active region std: 42.4100
Padding region std: 2.3094
  Enhancement: scale=1.250, mag 893.77 -> 1117.21
  Image edit mode detected: 1 reference latent(s)
Output change: mean=5.234821, max=1045.291038

The Output change line confirms the conditioning tensor was modified. If it shows 0.000000, no changes were applied.

Technical Details

• Model: FLUX.2 Klein 9B
• Text Encoder: Qwen3 8B (4096 hidden dim, 36 layers)
• Conditioning Shape: [batch, 512, 12288]
• Active Region: Positions 0-77 (determined by attention mask)
• Embedding Dimension: 12288 (likely 4096 × 3 concatenated representations)

Visual Results: Vanilla vs. With Flux2Klein-Enhancer

Exact same workflow, seed and prompt — only difference is using the node or not.
Click images to view full size.

source photo:

Comparison 1

Prompt: [turn only the ground into a mirror surface reflecting the sky, keep the full dog and it's body unchanged and add the dog's reflection below]

Vanilla Flux.2 Klein	With Enhancer Node

Comparison 2

Prompt: [replace the grass with shallow ocean water and add realistic water reflections of the dog, keep the sunny lighting]

Vanilla	With Enhancer Node

Acknowledgments

Built through empirical analysis of FLUX.2 Klein's conditioning structure using diagnostic tools to inspect actual tensor shapes and statistics during inference.