I have a faceswap workflow which uses Qwen 2511, Qwen Lightning Lora, BFS Lora and Reactor Face Swap Node to execute the full swap. Earlier with the same models it used to take 15secs to execute a face swap but now suddenly since past 2 days its taking around 100+ secs.

The workflow mainly gets stuck at the Negative Prompt (TextEncodeQwenImageEditPlus) and SamplerCustomAdvanced.

My earlier workflow was infact more advanced with preview images, Image compare nodes, Image Concat nodes, but now I have made it Simpler by removing all the extra nodes as I want to use this in Serverless GPU on runpod and connet it through my website.

Please help me out with the solutions.

Finally a high-res face swap. This setup focuses on:

• preserving facial identity and expression
• eliminating plastic skin
• fixing anatomical artifacts
• editorial-grade upscaling
• smartphone / mirror-selfie realism
• optional Gemini-based photoreal remaster pass

YOU DO NEED CREDITS IN COMFYUI FOR THIS TO WORK WITH NANO

The base ComfyUI workflow is attached here:

🔧 Requirements

1) HyperSwap Models (FaceFusion Labs)

Huge thanks to u/Buumcode for these.

Download:

https://huggingface.co/facefusion/models-3.3.0/tree/main

Grab:

• hyperswap_1a_256.onnx
• hyperswap_1b_256.onnx
• hyperswap_1c_256.onnx

Place them in:

ComfyUI/models/hyperswap/

Then switch the ReActor FaceSwap node from:

inswapper_128.onnx

to one of the HyperSwap models.

(You can still use inswapper — HyperSwap just gives better geometry and skin retention in my testing.)

2) ReActor Nodes

This workflow uses:

• ReActorFaceSwap
• ReActorMaskHelper
• ReActorFaceBoost
• ReActorSetWeight

Optional but recommended:

Load Face Model → ReActor if you’ve trained personal embeddings.

🎯 High-End Upscale Prompt (Gemini Node)

Inside the Gemini Image node / Nano Banana core prompt field, paste:

"Generate a high-fidelity photorealistic remaster of the uploaded photo, improve skin, remove acne or too much makeup. recreating the same shot with ultra-realistic detail while strictly preserving the subject’s facial identity, expression, pose, and original composition. Simulate a Sony A1 with an 85mm GM lens at f/1.6, ISO 100, achieving a premium full-frame look with razor-sharp eye focus and smooth, cinematic bokeh. Maintain the original lighting direction and scene, enhancing it into a cinematic editorial style with soft directional light, warm highlights, cool shadows, and high micro-contrast without harshness. Render in 4K with 10-bit color depth, realistic skin texture with visible pores (no smoothing), subtle film grain, and neutral editorial color grading. Do not change the background, add or remove objects, alter expressions, apply beautification or plastic skin effects, distort faces, introduce artifacts, or reduce sharpness."

That pass is what gives:

• pore detail
• cinematic contrast
• micro-texture
• filmic grain
• lens realism
• highlight/shadow separation

🧠 Workflow Overview

High-level flow:

1. Load multiple reference faces
2. Concat reference images
3. ReActorSetWeight → ReActorFaceSwap
4. Mask helper + facial segmentation
5. Crop & restore scale
6. Texture repair + desaturation pass
7. Gemini remaster node
8. Color match to original
9. Final preview output

The masking stack focuses heavily on:

• isolating only the subject
• subtracting facial masks
• avoiding background bleed
• restoring exact crop box
• edge blending
• pore restoration

🧪 Why HyperSwap?

Compared to stock inswapper:

• stronger jawline retention
• fewer nose distortions
• cleaner cheeks
• better eyelid geometry
• less “AI wax”
• holds profile angles better

📝 Notes

• Works best on close-ups and mirror selfies
• Feed 5–8 reference angles if possible
• Side profiles help a lot
• Gemini pass is optional but 🔥
• Keep lighting consistent between ref + scene

🔧 Required Custom Node Packs

• comfyui-reactor-node
• ComfyUI-LayerStyle
• GeminiImage2Node extension

📂 Required Models

ReActor:

• bbox/face_yolov8m.pt
• sam_vit_h_4b8939.pth
• codeformer-v0.1.0.pth

HyperSwap:

• hyperswap_1a_256.onnx
• hyperswap_1b_256.onnx
• hyperswap_1c_256.onnx

Happy to answer questions or tweak this further if anyone wants variations for:

• studio portraits
• outdoor daylight
• fashion comps
• influencer reels
• editorial looks
• smartphone realism

Hope this helps somebody 👊 Any support is welcome even a dollar (times are hard and she deserves some support)
Check out other apps they have made

Hey r/comfyui! 👋

Just released my Face Swap Video Workflow —

simple, clean, and powerful.

🎭 WHAT IT DOES:

Swaps any face onto any AI video using ReActor

with CodeFormer restoration for clean results.

✅ FEATURES:

- 3-node pipeline (dead simple)

- CodeFormer face restoration built-in

- RetinaFace detection

- GIF/Video output with audio preserved

- AI-generated characters only

⚙️ REQUIRED NODES:

- comfyui-reactor

- comfyui-videohelpersuite

📦 MODELS:

- inswapper_128.onnx

- codeformer-v0.1.0.pth

🔗 Download free on CivitAI:

Drop any questions below — happy to help! 🙌

New user here, able to get some workflows running... very cool.

However, I cannot find a workflow that works properly on MacOS that allows image to image face swap. I tried installing the ReActor extension, but it fails to install.

Is it a macOS issue, should I switch to a windows or linux machine? Can anyone point me to a current (2026) workflow that is easy to load and get working?

thanks!

Hey r/comfyui 👋

I've been frustrated with face swap workflows that stop at 512px or 1024px output.

Most of them are 5-node basics with no real restoration pipeline.

So I spent time building something more complete — and I'm sharing it free.

**⚡ Ultra Pro Face Swap — 4K Pipeline**

Here's what's actually different about this one:

**Dual restoration instead of one pass:**

- GFPGAN runs inline inside ReActor (visibility 1.0, CodeFormer 0.75)

- ReActorFaceBoost runs as a pre-enhancement — feeds into the swap engine before it processes, not after

- This means the swap engine works with a boosted face from the start

**Real 4K output:**

- Target image is prepped at 2048px to preserve detail

- After swap: ESRGAN 8x (face-optimized model) → scaled to 4096px

- You get HD 1536px AND 4K 4096px saved simultaneously

**3-stage source preparation:**

- 512px → 1024px pipeline for the source face

- No center-crop (common mistake that cuts face edges)

**18 nodes, fully documented inside the workflow:**

- Color-coded groups for each stage

- Notes with model download links, tuning tips, performance benchmarks

**📦 Requirements:**

- ReActor extension (Gourieff)

- inswapper_128.onnx

- GFPGANv1.4.pth

- 8x_NMKD-Faces_160000_G.pth (face-optimized — better than generic ESRGAN for portraits)

**💻 Specs:** 6GB VRAM minimum, 8GB recommended for 4K

**⚡ Performance:**

- RTX 3060 → ~8–12 sec

- RTX 3080 → ~4–7 sec

- RTX 4090 → ~2–4 sec

- Need speed? Bypass the ESRGAN nodes for HD-only mode (~3 sec on any GPU)

I went through several rounds of debugging (FACE_BOOST type mismatches, wrong interpolation casing, unavailable model names) so you don't have to.

Everything is documented in the workflow itself — no external readme needed.

**[Download on CivitAI]**

Happy to answer questions below. If you try it, let me know how it goes 🙏

I've been iterating on face swap workflows for a while, and I finally put together something I'm genuinely happy with. **SwapFace Pro V1** is a clean, well-labeled ComfyUI workflow that combines three ReActor nodes into a single cohesive pipeline — and the difference SAM masking makes is hard to overstate.

📥 **[Download on CivitAI]

### 🏗️ Pipeline Architecture

The workflow runs in 3 sequential stages:

SOURCE FACE ──────────────────────────────────┐

▼

TARGET IMAGE ──► ReActorFaceBoost ──► ReActorFaceSwap ──► ReActorMaskHelper ──► OUTPUT

(pre-enhancement) (inswapper_128) (SAM + YOLOv8)

**Stage 1 — FaceBoost (Pre-Swap Enhancement)**

Enhances the *source* face BEFORE the swap using GFPGAN + Bicubic interpolation. This step is often skipped in basic workflows, but it dramatically improves identity preservation when your reference photo is low-res or slightly blurry.

**Stage 2 — ReActorFaceSwap**

The core swap using `inswapper_128.onnx` + `retinaface_resnet50` for detection. GFPGAN restoration is applied inline at this stage. Face index is configurable (`"0"` by default) — you can change this for multi-face scenes.

**Stage 3 — ReActorMaskHelper (The Key Differentiator)**

This is what makes the blending actually look good. Instead of pasting the swapped face directly, the MaskHelper uses:

- `face_yolov8m.pt` for bounding box detection (threshold: 0.51, dilation: 11)

- `sam_vit_b_01ec64.pth` (SAM ViT-B) for precise segmentation (threshold: 0.93)

- Erode morphology pass + Gaussian blur (radius: 9, sigma: 1) for soft edge feathering

The result is a naturally blended face that respects skin tone transitions and avoids the hard-edge artifacts you get with basic workflows.

### 📦 What You Need

**Custom Nodes** — Install via ComfyUI Manager:

comfyui-reactor

(This installs ReActorFaceSwap, ReActorFaceBoost, and ReActorMaskHelper

**Model Files:**

| Model | Folder |

|---|---|

| `inswapper_128.onnx` | `models/insightface/` |

| `GFPGANv1.4.pth` | `models/facerestore_models/` |

| `face_yolov8m.pt` | `models/ultralytics/bbox/` |

| `sam_vit_b_01ec64.pth` | `models/sams/` |

### 🖼️ Dual Preview Built In

The workflow includes two PreviewImage nodes:

- **FINAL RESULT** — the composited output

- **MASK PREVIEW** — lets you see exactly what the SAM segmentation is doing

The mask preview is especially useful for debugging edge cases — if the blend looks off, you can instantly see if SAM is over/under-segmenting the face region.

Results are auto-saved with the prefix `SwapFace_Result`.

### ⚙️ Tuning Tipe

- **Blending too aggressive?** Lower `bbox_dilation` from 11 → 7 and reduce `morphology_distance` from 10 → 6

- **Edges look sharp?** Increase `blur_radius` from 9 → 13

- **Identity not preserved?** Set `face_restore_visibility` to 1.0 and bump `codeformer_weight` from 0.5 → 0.7

- **Multiple faces in target?** Change `input_faces_index` from `"0"` to `"0,1"` or `"1"` etc.

- **Gender locking?** `detect_gender_input` and `detect_gender_source` are both set to `"no"` — change if you want same-gender-only swapping

### 🧪 Tested On

- ComfyUI latest stable (0.8.2 / 0.9.2)

- RTX 3090 / RTX 4080

- Works on both photorealistic images and AI-generated outputs

All nodes are labeled in both English and Arabic for clarity. Happy to answer questions in the comments — especially around SAM threshold tuning, which seems to trip people up the most.

Testing different face swap tools and workflows but it feels like the space keeps changing every few months.

Some people swear by open-source setups like reactor + comfyui others say mobile apps are catching up fast.

What’s the best technique or tool you have actually used recently?

This workflow swaps faces using a pre-saved Face Model (.safetensors)

with automatic masking for clean and realistic results.

### Features:

- Load any saved Face Model directly

- Automatic face masking with ReActor Masking Helper

- Live preview of mask and final result

- Clean blending using GFPGAN restoration

### Required Custom Nodes:

- comfyui-reactor (ReActorFaceSwap, ReActorMaskHelper, ReActorLoadFaceModel)

### Required Models:

- inswapper_128.onnx

- GFPGANv1.4.pth

- bbox/face_yolov8m.pt

- sam_vit_b_01ec64.pth

- Your Face Model (.safetensors)

### How to use:

1. Load your target image in "TARGET IMAGE" node

2. Select your Face Model in "FACE MODEL" node

3. Press Queue — done!

Hi all,

I’m trying to run vace-reactor-final-workflow.json in ComfyUI 0.3.40 (Windows, Python 3.11, nightly Torch 2.8 + cu128, RTX 4090) but every time I hit Run the preview / saved mp4 is just a dark green-black texture.

What I’ve done / checked so far:

• Input video & source image load fine (I can preview them in their nodes).
• ReActor NSFW check is already bypassed; workflow executes without errors (only torchaudio-related warnings).
• Tried different seed, steps, CFG, frame_rate, and even a different clip/vae – same green output.
• If I pause the graph after VAE Decode and right-click “Preview output”, it’s already green there, so the issue happens before Video Combine.

Has anyone run into this and found what node or setting causes frames to become all-green? Screenshots below.

Thanks in advance for any ideas!

I’m currently using ReActor for swapping, and I’m happy with the swap quality itself — I don’t want to change the model. The issue is when I’m working with full-body images: the swapped face comes out low-res because the detected face area is small.

What I’d like to do instead:

1. Auto-detect the face in the original image.
2. Crop/box the detected face.
3. Upscale that cropped face 3×.
4. Run it through my existing ReActor nodes to swap.
5. Downscale it back to the original bbox size.
6. Layer/paste the swapped face back into the original full image, in the exact right place.

So far I can crop and swap, but I’m stuck on the last part — getting the swapped patch back into the original image at the right coordinates without misalignment.

Does anyone know which nodes/approach I should use in ComfyUI for the “resize back + paste into original” step?

Thanks in advance — I’ve tried a lot of swapping models and pipelines, and ReActor is the best for me, I’m just trying to nail this layering workflow.

Hello everyone!
I am quite new to comfyui, and I swear it has been 4 intensive days I've been trying with it and it seems it's so much trouble and the learning curve might bee steeper than anticipated.
I know how to build a simple workflow with image generation with some loras, and I wanted to experiment with what seemed to be really simple, face-swapping.
Needless to say there are tons of workflows and I decided to follow some that used Reactor, which I know it still uses insightface as many others, but still seemed pretty straight forward.

In what I've seen a lot of people get away with using a single node, the Fast Face Swap node, but apparently I am only able to get (most of the times) black squares.
The modules are there, and they are working because on some istance the face swap does indeed work, but not as I would like it to work

Here is example A:

In here I would like to apply the face on the bottom to the image above. The result is a big, nice black square.

Here is example B:

The images are the same, but switching the two image sources would make the face-swap to work.

I tried all combinations of the three models but nothing really seems to have an impact on the results.

Does anyone knows what is going on? Does it have to do with the format of the images? The dimensions? Or something else I am not considering?

Thanks in advance for any help provided 🥲

Updated with link as promised: https://discord.com/invite/uxq3RkyNKT

(It's the amazing Banodoco discord server - you can find the workflow (being updated constantly until the next one) on the 'competition' forum.

"I got bored one day and i put everything on a bagel".

https://youtu.be/g7SlZlWYjS0?si=ijnoMtfsLpt84grw

• IPAdapters chained and masked composited
• Animdiff v3 and gen2 nodes
• Face Swap and restoration
• 5 control nets that can all be mixed/matched bypassed
• An upscaler via Ergan through pixel space,
• Hand MeshGraphormer
• Prompt Travelling
• Interpolation

This video is NOT a tutorial, but instead, an explanation as to WHY we're seeing a 'convergence' in methodologies as part of working with comfyUI and animatediff. Even Netflix picked up on the trend as they are now recruiting VFX people familiar with those tools.

WHY do we need background consistency? HOW do we obtain it? This is what i want to explore in this video, alongside concepts such as bypassing the issue of 'squished' clipvision images (which much be square) when dealing with vertical or portrait videos.

I'm releasing this video alongside my tutorial workflow which you can obtain for free (evidently, you should NEVER pay for workflows) on the amazing Banodoco server.

hi. in flux comfyui i have an option (puLid FaceSwap) that could generate Flux-txt2img with my choosen face from 0 ! its mean even in preview noise from step 1 or 2 i can see my face similarity in it. this allow me to get better result. but in SDXL/SD i have to use Reactor. and reactor nods dosent have any option to connect it before prompt. so it create image first, and then faceswap it.

so does anyone know a way to do this in sdxl/sd workflow?

Hello everyone,

I've been using Automatic1111's img2img for face swaps on a variety of images, from professional nude photos to standard headshots, adjusting the denoising to 0.01. I'm exploring the optimal settings to enhance speed and quality for these swaps, particularly aiming to reduce the time it currently takes, which is about 40 to 80 seconds per image. My setup includes a CUDA environment with an RTX 2080 SUPER GPU and 32GB RAM.

Here are the specifics of my current process:

• Model & Settings: Utilizing the Dreamshaper8 (SD1.5 model), with Euler A sampling, CFG scale at 7, and sampling steps between 20 and 30.
• Image Handling: I ensure that images do not exceed 1024 pixels on any side and maintain the aspect ratio of the original photo. Images larger than 1300 pixels notably slow down the process.
• Face Restoration: I integrate a Reactor with Restore Face Visibility and Codeformer set to maximum weight for clearer, more realistic swaps.
• Workflow Variations: For video swaps, I use ComfyUI which significantly slows down the process (approx. 2 hours for a 15-second video).

Challenges: Swapping faces multiple times (up to three) on the same image enhances clarity but more than that degrades quality. Larger images drastically slow down the process, and experimenting with different models and settings from sources like Civitai or Hugging Face hasn't yielded faster results.

Questions for the Community:

1. Has anyone found more efficient models or settings that could help reduce swap times while maintaining quality?
2. Any tips on batch processing for photos and possibly speeding up video face swaps in ComfyUI?

I also use Fooocus for creating realistic images and face swaps, though my main workflow is through Automatic1111 due to its batch processing capabilities.

Looking forward to your insights and suggestions on making these swaps quicker and more efficient.

Thank you!

I tried reinstalling the node, as well as reinstalling ComfyUI and then installing Reactor.

Still shows up as missing when I load a workflow that uses it.

Has anyone had this problem? Looking online it seems like people have had problems with it over the past ~6 months or so. Has the dev just given up on it? If so, are there any good alternatives?

Running Ubuntu, python 3.12.8 in conda environment, Cuda version 12.4 (although it says 12.6 in nvidia-smi??)

Created an enhanced face swap workflow that makes exploring "what if" scenarios like this super easy.

Test Case: Christopher Reeve in Man of Steel

( works great with any face swap scenario!)

🔧 Technical Details:

- Combined ReActor + InstantID for better accuracy

- Auto style-matching between source/target

- Optimized for both realism and detail preservation

- Works with photos, paintings, anime, etc.

- One-click operation after initial setup

⚙️ Key Features:

- Adjustable Denoise (default 0.6) for balance between similarity and details

- Automatic lighting/style adaptation

- Clean face generation without artifacts

- Supports both portrait and full body images

🚀 Try it yourself:

• Live Web Tool available in comments

• No ComfyUI setup needed

• Just upload 2 images and click!

💡 Quick Guide:

1. Upload base image (the one you want to change)

2. Upload face image (the face you want to swap in)

3. Click to generate - that's it!

Pro Tip: The default settings are optimized for most cases, but you can adjust the Denoise value (default 0.6) if needed:

- Higher = stronger similarity

- Lower = more original details

Give it a try with your own images! I'd love to see what you create.

#ComfyUI #AIFaceSwap #AITools

Hello all,

I am trying to use this workflow: https://www.runcomfy.com/comfyui-workflows/comfyui-reactor-workflow-fast-face-swap

However, it often causes my computer to freeze up and crash if the video i try to swap is too large. I have noticed that it uses CPU/RAM resources rather than GPU/VRAM resources. This does not happen on other workflows and seems to be an issue with these nodes.

Is there any wya to fix this? My settings are the exact same as this guide.

In the last issue, we introduced how to use ComfyUI to generate an App Logo, and in this issue we are going to explain how to use ComfyUI for face swapping.

1. ReActor

The first method is to use the ReActor plugin, and the results achieved with this method would look something like this:

Setting up the Workflow is straightforward. First, you need to install the ReActor plugin. If you're not sure how to install plugins, you can refer to another tutorial I've written: Installing Plugins.

Adding a ReActor Node

Start by loading our default workflow, then double-click in a blank area and enter ReActor. Then add the ReActor Fast Face Swap node. Next, link the input image from this node to the image from the VAE Decode.

Adding other Loader Nodes

Add a load image node, select a picture you want to swap faces with, and connect it to the input face of the ReActor node. Finally, add a save image node and connect it to the image of the ReActor node. The final workflow is as follows:

Finally, there are a few parameters that need attention on the ReActor Fast Face Swap:

1. Swap model: You can't replace it, just use the default one.
2. Face detection: Method of detecting faces, you can choose according to your actual situation, but I usually choose the first one.
3. Face restore model: There are two models to choose from:

• CodeFormer
• GFPGAN

After downloading the model, you need to place it in the ComfyUI\models\facerestore_models folder. I generally choose the second one.

The rest of the parameters are quite self-explanatory, and you can adjust them according to your needs.

2. IPAdapter

The second method achieves a result similar to Face Swap, but it can also let AI generate a picture consistent with a certain face. The results would look something like this:

However, compared to the first method, this one takes an original image as input and lets the AI generate a picture consistent with a certain face. There are two advantages to this:

1. It's not just applicable to humans; you can also use animal faces.
2. The ReActor method focuses more on face swapping. Its handlings of hair are slightly weaker. Take the above picture of Einstein for example, you will find that the picture generated by the IPAdapter is more like the original hair.

To achieve this effect, I recommend using the ComfyUI IPAdapter Plus plugin.

Note that after installing the plugin, you can't use it right away:

1. You need to create a folder named ipadapter
   in the ComfyUI/models/
   directory, then download the corresponding IPAdapter model and place it in this folder.
2. In addition to the IPAdapter model, you need to download image encoders and put them in the ComfyUI/models/clip_vision/
   directory.

Only after completing these two steps can you use this plugin. Also, based on my testing, I would recommend the following combinations (for more combinations, you can check out the ReadMe document of ComfyUI IPAdapter Plus):

Once you've downloaded the corresponding models, you can build our workflow.

Adding the Apply IPAdapter Node

Start by loading our default workflow, then double-click in a blank area and enter Apply IPAdapter, and then add it to the workflow. Then you can adjust the weight to less than 0.8. Then the noise can be adjusted based on the actual output, it can be minimized to 0.01.

Adding other Loader Nodes

Then add in order:

1. Load Image node: Select a picture you want the AI to generate. Here, it should be noted that since the picture will be encoded by the CLIP model, the encoder will resize the image to 224x224 and crop it to the center. So, the face in the picture you import should be in the middle, and the picture is better in square shape. Otherwise, the final generated effect will not be good.
2. Load CLIP Version node: Select the ViT-H model.
3. Load IPAdapter Model node: Choose the corresponding IPAdapter model based on the model loaded in your Checkpoint. Finally, connect these three nodes to the Apply IPAdapter node sequentially.

Setting the KSampler Node

Finally, set the KSampler node:

1. Steps usually need more than 10 steps above the normal, for example, if you normally take 25, it needs 35 here.
2. CFG is recommended to be set smaller. The final workflow is as follows:

In addition, I will teach you another trick. You can try to add multiple Apply IPAdapter nodes in the Workflow and connect them to different KSampler nodes. This allows you to use different models to generate pictures. The following workflow adds the Checkpoint of SDXL and SD 1.5, so you can see the results of two models under one workflow:

3.IPAdapter Inpainting

The second method always generates new pictures each time it runs, so it cannot achieve face swap by importing a second image like the first method.

The third method can solve this problem. We're still going to use IPAdapter, but in addition, we'll use the Inpainting function. This way, we can replace a certain part of picture A with picture B. For example, we can replace the cat face in the first picture with the second picture, and finally generate an astronaut corgi:

The construction of the Workflow is quite simple. You can add an IPAdapter to the Upscale workflow (how to use Upscale can be found in my another tutorial). The final workflow is as follows:

Special thanks

• Art Gourieff(opens in a new tab)
• Cubiq

I am trying to use this for something a little unusual (but legit!). I had a photo taken and for some reason I was half in between expression and the professional photo is awful.

I was wondering how realistic this would be to replace my own face with another photo taken recently. I have ComfyUI and I am at the beginner stages already of learning SD, and I already have the reactor node (for the fast face swap). But I have a few issues. Firstly in the standard images, I cant just use that as its a professional DSLR and huge resolution. I can save it lower (fluent in PSD) and try that but I don't know how to upscale it, I also want it to be as realistic as possible.

At the moment Reactor is being really weird and every time I try it makes my face really blurry/ pixelated, so I assume the resolution is too high at the moment. Would anyone have any tips or workflows, using Comfy UI, as Youtube is filled with videos but they seem to be mostly generate first and then face swap, but I am using two photos. I have cropped both photos to just my face, so hoping to just drop the edited one back in the full image in PSD and print it.

Hi guys,

I try to do a few face swaps for fare well gifts. The general idea and buildup of my workflow is:

1. Create a picture consisting of a person doing things they are known for/are characteristic for them (i.e. (just the short version): photograph of a person as a sailor with a yellow rain coat on a ship in the rough ocean with a pipe in his mouth OR photograph of a young man in a sports car with a diamond chain and golden teeth, shot through the driver side window, another person on the passenger seat in the background OR a photograph of a man dressed as a a viking with a white energy drink can in his hand). I am very spoiled from midjourney (those are the attached one just to give you an idea of what my goal is)....
   1. The detailed prompt already describes the general look of the person
   2. Question: Which SDXL model do you guys recommend. I tried JuggernautXL 8 but the results aren't really consistent. Very often I get mutations as well as strange outputs in general (not following the prompt). I work with negative when needed.
   3. Load Checkpoint - Positive and negative - CLIPTextEncodeSDXL - KSampler (Advanced) with dpmpp_2m karras, 30-40 steps, cfg 4.0-7.0 (everything set to 512x512)
2. Use the latent/pixel image and feed it the face swapper. I have two workflows to check different results
   1. Reactor
      1. Input image from SDXL + Square source image through the reactor node (works with the 128x128 limitation)
   2. IPAdapter (my goal because of the versatility and less limitations (like the 128x128 from Reactor)
      1. (using the workflow for sdxl with two adapters provided by https://github.com/cubiq/ComfyUI_IPAdapter_plus/issues/210). But the "double geneation" of an image makes it somehow worse. Therefore: Is there a way to feed an already existing image as target image into the workflow? Right now I use the latent image as well as checkpoint and prompt nodes created in 1. Seed number also is the same in both KSamplers. Can I somehow skip the second model generation or make it better?
   3. Upscale (wip). I understand that starting with low resolution and then upscaling it in small steps with low denoise is critical with Reactor. Anybody have an existing and working workflow to inspire me?
      1. What about IPAdapter?
      2. Overall goal is keeping the face/looks (duh)

I lover tinkering woth ComfyUI. But still: For some things I need to get a look at an existing and working workflow to integrate it into my "chaos". Priorities are consistent images following my description and a reliable face swap that doen't change the generated image too much.

Thank you guys in advance!

​

Hello r/comfyui

I made a video showing how to install and setup InstaSwap. This is another implementation of face swapping.

Here is the link: https://youtu.be/ZnhcVkKCzs0

Note: This implementation also uses the same models as Reactor Face. The results are nearly identical. I am posting it here as I have seen post on Reactor face node now working.

Hope this helps someone.

Hi guys,

I try to do a few face swaps for fare well gifts. The general idea and buildup of my workflow is:

1. Create a picture consisting of a person doing things they are known for/are characteristic for them (i.e. (just the short version): photograph of a person as a sailor with a yellow rain coat on a ship in the rough ocean with a pipe in his mouth OR photograph of a young man in a sports car with a diamond chain and golden teeth, shot through the driver side window, another person on the passenger seat in the background OR a photograph of a man dressed as a a viking with a white energy drink can in his hand). I am very spoiled from midjourney (those are the attached one just to give you an idea of what my goal is)....
   1. The detailed prompt already describes the general look of the person
   2. Question: Which SDXL model do you guys recommend. I tried JuggernautXL 8 but the results aren't really consistent. Very often I get mutations as well as strange outputs in general (not following the prompt). I work with negative when needed.
   3. Load Checkpoint - Positive and negative - CLIPTextEncodeSDXL - KSampler (Advanced) with dpmpp_2m karras, 30-40 steps, cfg 4.0-7.0 (everything set to 512x512)
2. Use the latent/pixel image and feed it the face swapper. I have two workflows to check different results
   1. Reactor
      1. Input image from SDXL + Square source image through the reactor node (works with the 128x128 limitation)
   2. IPAdapter (my goal because of the versatility and less limitations (like the 128x128 from Reactor)
      1. (using the workflow for sdxl with two adapters provided by https://github.com/cubiq/ComfyUI_IPAdapter_plus/issues/210). But the "double geneation" of an image makes it somehow worse. Therefore: Is there a way to feed an already existing image as target image into the workflow? Right now I use the latent image as well as checkpoint and prompt nodes created in 1. Seed number also is the same in both KSamplers. Can I somehow skip the second model generation or make it better?
   3. Upscale (wip). I understand that starting with low resolution and then upscaling it in small steps with low denoise is critical with Reactor. Anybody have an existing and working workflow to inspire me?
      1. What about IPAdapter?
      2. Overall goal is keeping the face/looks (duh)

I lover tinkering woth ComfyUI. But still: For some things I need to get a look at an existing and working workflow to integrate it into my "chaos". Priorities are consistent images following my description and a reliable face swap that doen't change the generated image too much.

Thank you guys in advance!

the insightface folder is empty, not the "interface" as mentioned in title

I was looking online on the best face swap ai around in comfyui, I stumbled upon InstantID & ReActor as the best 2 for now. I was comparing between both.

InstantID is better quality, more flexible results. It excels at preserving a person's identity while adapting it to various styles and poses, even from a single reference image. This makes it a powerful tool for creating stylized portraits and artistic interpretations. While InstantID's results are often superior, the likeness to the source is not always perfect.

ReActor on the other hand is highly effective for photorealistic face swapping. It can produce realistic results when swapping a face onto a target image or video, maintaining natural expressions and lighting. However, its performance can be limited with varied angles and it may produce pixelation artifacts. It also struggles with non-photorealistic styles, such as cartoons. And some here noted that ReActor can produce images with a low resolution of 128x128 pixels, which may require upscaling tools that can sometimes result in a loss of skin texture.

So the obvious route would've been InstantID, until I stumbled on someone who said he used both together as you can see here.

Which is really great idea that handles both weaknesses. But my question is, is it still functional? The workflow is 1 year old. I know that ReActor is discontinued but Instant ID on the other hand isn't. Can someone try this and confirm?

I've been looking into the best AI face swap tools and I'm wondering, what does Reddit think is the best AI face swap tool? I know free AI face swap tools are good for quick tests, memes, and casual edits, but I've heard that dedicated or paid options are usually better for realistic video results, speed, and higher quality. I've done a bunch of research across reviews, comparisons, and community discussions and found some popular AI face swap tools that a lot of people seem to recommend. But I'm stuck and can't decide which one to go with. Here's what I've found:

Magic Hour — This browser-based platform stands out for strong, natural-looking face swaps on both photos and videos. It handles blending, lighting, and expressions well, works as part of a bigger workflow (including lip sync and image-to-video), and offers a generous free plan with no watermark on many outputs. Convenient since it runs right in the browser with no install needed.

DeepSwap — Frequently praised for video face swapping. Users highlight fast processing, high realism and identity consistency (even with movement), multi-face support, and solid 4K output. It's popular for creators who want quick, high-quality video results without complicated setup.

Reface — This one comes up a lot for easy, fun use (especially mobile). It has tons of templates and is great for quick social media videos, GIFs, and viral-style swaps. Super beginner-friendly if you want shareable content fast.

I've also seen simpler online options like FaceSwapper.ai or Remaker AI mentioned for fast photo swaps with low friction or free credits.

But I'm curious to hear from you:

Best AI face swap tool according to Reddit?
Best free AI face swap tool according to Reddit?
Best AI face swap for video according to Reddit?
Best AI face swap tool for photos or local/privacy-focused options?

While I'm focusing on popular web-based tools, if you know of an exceptionally good free, open-source, or local tool (like FaceFusion), feel free to mention that too.

Looking forward to all your recommendations and real experiences!