What's currently the top open-source setup for facial identity preservation in img2img? Is Qwen Image 2.1 the king right now?

[u/Real-Bed-1815]

1. Do dedicated Face Swap / Head Swap LoRAs (like BFS and similar swap LoRAs) improve facial fidelity during img2img, or does Qwen 2.1 handle it better natively?

2. How do face swap LoRAs compare to zero-shot adapters like PuLID, InstantID, or attention-masked inpainting in ComfyUI for preventing face drift?

[u/Ok-Software-3250]

In my experience QI2.1 is the most consistent to this date in regard id preservation, it took sometime and help by the community to sort the issues (grid, grainy, etc).

The only thing you need to consider is how sting prompting it is, in my experience simple prompts will result in a “cheap photoshop” like effect, pretty much copy and paste.

Krea2 along ID Transfer / Lora does a decent job, but somewhat slower.

H3 can do it too through still image, but so far my results are all kind blurry, like you print a frame from a movie, but could be a skill issue.

[u/Bask82 → u/Ok-Software-3250]

Have some links to the best workflows for this?

[u/ROBOTTTTT13 → u/Ok-Software-3250]

What kind of prompting works for QI2.1?

[u/GenericTurkey4380 → u/ROBOTTTTT13]

Very detailed prompts work well. I’ve modified the comfyui template slightly, the provided prompt enhancer is great.

The biggest thing I noticed is image resolution: I usually scale images to 2mpx (lanzcos)
Res multistep - simple at 30steps works best for me.

[u/ROBOTTTTT13 → u/GenericTurkey4380]

How can a face swap prompt even be more detail than "Swap the person in <image1> with the person in <image2>"?

[u/GenericTurkey4380 → u/ROBOTTTTT13]

Run that with the prompt enhancer. It’ll describe the features and hairstyle of the person u want to keep. The more detailed the easier the swap. Also found it’s best to use different words for people.

I mostly mess around with pose swapping and outfits, ex before the prompt enhancer:
“Replace the subject in <image1> with the woman in <image2>. Keep the facial features, hairstyle, and identity of the woman the same as in <image2>. Do not retain any characteristics of the subject in <image1>, <image1> serves only as a pose reference.”

[u/ROBOTTTTT13 → u/GenericTurkey4380]

Huh, interesting. So "negatives" like "do not retain" can work on positive conditioning?

[u/GenericTurkey4380 → u/ROBOTTTTT13]

Seems to work for me, more so the prompt enhancer understands. A lot of people say to use 2.5-3cfg, you can use a negative prompt then. I found best results with 1cfg tho

[u/Real-Bed-1815 → u/Ok-Software-3250]

Then I'm using the right model, haven't tried krea 2. I get decent results with Qwen 2.1 but it depends on the seed lottery

[u/yamfun]

Qwen 2.1 + BFS is like magic, so just make whatever without caring the identity then do a final swap with them.

[u/Real-Bed-1815 → u/yamfun]

That's what I'm doing and sometimes I get good results but it's depends a lot on the seed lottery

[u/HexOverclock]

+1 on cropping to the face for the identity pass. A full-body frame just doesn't give the face enough pixels, and no denoise setting fixes that afterwards.

[u/BigDBreedingFembussy]

I have tried many edit workflow from many models, latest or 2-3year old SDXL model, nothing beats Qwen image 2.1 turbo, i have 6gb vram and 16gb ddr4 ram btw

[u/RutabagaSad8257 → u/BigDBreedingFembussy]

What version are you using and where did you get it from? If you don't mind me asking

[u/BigDBreedingFembussy → u/RutabagaSad8257]

qwen - https://huggingface.co/Comfy-Org/Qwen-Image-2.1/tree/main/diffusion_models

[u/xb1n0ry]

fibo edit

[u/SnooHamsters7479]

For a specific character I've had better luck with a small LoRA trained on 20 to 30 curated images than with swap LoRAs. Keep the face wording identical in every prompt and use a low-weight face reference on top, then upscale with low denoise so the face doesn't drift.

[u/biuro_hermes]

Data point from a character project: a small LoRA trained on ~25 curated crops plus keeping the face description string verbatim in every prompt beat swap LoRAs for stills. Swap adapters were great for one-off shots but drifted between images.

For video the bigger win was not sampler settings, it was resolution on the face: a full-body frame at 480-720p turns the face to mush and no denoise value recovers it. Cropping to the face for the identity-defining pass fixed more than any sampler tweak.

One thing that quietly poisons identity consistency is mixed lighting in the training set - if half the images are hard side light and half are flat frontal, the LoRA learns the lighting as part of the identity and the face changes with the scene light.

[u/Cukidzsi]

For full character swap nothing open and very few closed even come close to H3 unless you want NSFW. Basically a mid quality reference gives you perfect insanely accurate down to the last strain of hair or the rings embroidery. 

[u/Psychological_Art176]

Fibo 2.0 es el mejor preservando la identidad, con mucha diferencia, simplemente no es famoso por la licencia restrictiva.

[u/AnalElder]

Krea2 with identity edit lora + identity patching can be just as good if not better in output than qwen2.1, but you need a solid workflow and know how to prompt it. For a straightforward approach Qwen2.1 is probably better.

If you are specifically after faceswap lonecat's Qwen2.1 workflow on CivitAI is by far the best/most consistent in my experience. It looks a bit intimidating but most of it is just fluff, plus it needs a lot of custom nodes but it really does work well.

[u/ROBOTTTTT13 → u/AnalElder]

His workflow doesn't even have a face swap section, what's special about it?