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    FLUX.2 Klein 9B - Reference-Based Face Swap Workflow - v1.0
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    FLUX.2 Klein 9B - Reference-Based Face Swap Workflow

    ⚡ Production-tested workflow.

    This workflow originated from an internal automation pipeline capable of processing hundreds of images automatically through the ComfyUI API on a single NVIDIA T4 GPU.

    A highly consistent face swap workflow for ComfyUI built around FLUX.2 Klein 9B, latent references, and a dedicated face swap LoRA.

    Unlike traditional face swap methods, this workflow uses both a Target Reference and a Source Face Reference to preserve composition while transferring identity.


    Requirements

    Before loading the workflow, make sure you have:

    • FLUX.2 Klein 9B

    • FLUX2 VAE

    • Qwen 3 8B FP8 Mixed Text Encoder

    • Face Swap LoRA

    • LanPaint Custom Nodes


    Required Models

    FLUX.2 Klein 9B

    Place inside:

    ComfyUI/models/unet/
    

    Model:

    flux-2-klein-9b.safetensors
    

    FLUX2 VAE

    Place inside:

    ComfyUI/models/vae/
    

    Model:

    flux2-vae.safetensors
    

    Qwen 3 8B FP8 Mixed

    Place inside:

    ComfyUI/models/text_encoders/
    

    Model:

    qwen_3_8b_fp8mixed.safetensors
    

    Face Swap LoRA

    Place inside:

    ComfyUI/models/loras/
    

    Model:

    bfs_head_v1_flux-klein_9b_step3500_rank128.safetensors
    

    Required Custom Nodes

    LanPaint

    This workflow uses the LanPaint sampler.

    Install it through:

    ComfyUI Manager → Install Missing Custom Nodes


    Workflow Overview

    This workflow uses two different references:

    Target Reference

    Preserves:

    • Composition

    • Pose

    • Framing

    • Perspective

    • Scene structure

    • Lighting context

    Source Face Reference

    Transfers:

    • Face identity

    • Facial proportions

    • Hair characteristics

    • Eyes

    • Skin details

    By combining both references, the workflow achieves significantly better consistency than traditional face swap approaches.


    How To Use

    Step 1 - Load The Source Face

    Node:

    Source Face Image

    This image provides the identity that will be transferred.

    Recommended:

    ✅ Front-facing portraits

    ✅ High-resolution images

    ✅ Clear facial visibility

    ✅ Good lighting

    Avoid:

    ❌ Motion blur

    ❌ Heavy occlusions

    ❌ Sunglasses

    ❌ Extreme angles


    Step 2 - Load The Target Image

    Node:

    Target Image

    This image provides:

    • Background

    • Body

    • Clothing

    • Pose

    • Composition

    • Framing

    • Perspective

    The workflow attempts to preserve these elements while replacing the identity.

    Recommended:

    ✅ Portrait photos

    ✅ Medium shots

    ✅ Visible face

    ✅ Clear lighting

    Avoid:

    ❌ Tiny faces

    ❌ Hidden faces

    ❌ Extreme side profiles


    Step 3 - Queue Prompt

    Press:

    Queue Prompt

    The workflow automatically:

    1. Reads target dimensions

    2. Creates target latent references

    3. Creates source face latent references

    4. Applies dual-reference conditioning

    5. Generates the face-swapped result

    6. Preserves original scene composition

    No additional setup is required.


    What This Workflow Preserves

    • Original background

    • Original composition

    • Original lighting

    • Original perspective

    • Original pose

    • Original framing

    • Original camera distance

    • Original scene layout


    Ideal Use Cases

    • UGC Creator Replacement

    • Influencer Face Swaps

    • Character Consistency

    • Marketing Creatives

    • AI Avatars

    • Personal Branding

    • Dataset Generation

    • Batch Face Swap Pipelines


    Performance

    Tested on:

    • NVIDIA T4

    • RTX 3060

    • RTX 4070

    • RTX 4090

    VRAM requirements will vary depending on image resolution.


    Batch Automation

    This public release contains the single-image workflow.

    Internally, I use a custom Python automation system connected directly to the ComfyUI API that can process large batches automatically.

    Example setup:

    • 1 source face

    • 400+ target images

    • Automatic queue management

    • Automatic retries

    • Organized output folders

    • GPU-friendly processing

    • Designed for T4 cloud instances

    This automation system is not included in the public release.


    Commercial Applications

    This workflow can be used for:

    • UGC generation

    • Marketing campaigns

    • Creator replacement

    • Character consistency projects

    • AI influencer pipelines

    • Content automation


    Need Batch Processing?

    I also develop custom automation systems built around ComfyUI.

    Examples:

    • Face swap automation

    • Folder-based processing

    • ComfyUI API integrations

    • Large-scale image generation pipelines

    • Dataset creation workflows

    • Custom workflow development

    If you're interested in automation or custom solutions, feel free to send me a direct message on Civitai.


    Credits

    Built and tested using FLUX.2 Klein 9B, latent reference conditioning, and a dedicated face swap LoRA for high-consistency identity transfer.

    If you find this workflow useful, consider leaving a rating and sharing your results.

    Description

    Initial release.

    Reference-based face swap workflow for FLUX.2 Klein 9B using dual latent conditioning.

    Features:

    - Source face reference

    - Target composition reference

    - Face swap LoRA integration

    - LanPaint sampling

    - Automatic target size detection

    - High composition preservation

    Designed for single-image face swaps and compatible with large-scale automation pipelines through the ComfyUI API.

    FAQ

    Workflows
    Flux.2 Klein 9B

    Details

    Downloads
    359
    Platform
    CivitAI
    Platform Status
    Available
    Created
    6/5/2026
    Updated
    6/22/2026
    Deleted
    -

    Files

    flux2Klein9BReference_v10.json

    Mirrors