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Qwen Image 2.1 Outfit Swap Consistency LoRA

8585°
Qwen Image 2.1 Outfit Swap Consistency LoRA
Created by
AusBoss
on Civitai
by AusBoss - Qwen Image 2.1 Outfit Swap Consistency LoRA - Qwen Image 2.1 can already dress a person in the outfit from another picture. The result comes back a few pixels off, the face a little softer, the background repainted. With this LoRA only the clothes change. No trigger word. Load it at strength 1.0, give the person as image 1 and the outfit as image 2, and ask for the swap
Creator notes
A consistency LoRA for outfit swaps with Qwen Image 2.1: the person gets the outfit from a second picture, and the rest of the picture stays where it was. Qwen Image 2.1 can already dress a person in the outfit from another picture. The result comes back a few pixels off, the face a little softer, the background repainted. With this LoRA only the clothes change. No trigger word. Load it at strength 1.0, give the person as image 1 and the outfit as image 2, and ask for the swap: Dress the person in image 1 in the shown in image 2. Keep their face, hair, hands, pose and the background exactly the same. Why use it Qwen Image 2.1 can do an outfit swap without this LoRA. This is what the LoRA changes, measured on 16 swaps it never trained on, same seed and request: - The picture stays in place. Without the LoRA the result sits 3.6 px away from your picture, so it no longer lines up with the original. With it: 0.1 px. - The face stays the same. Without: 14.1 % of the face's pixels change noticeably. With: 1.7 %. - The background is left alone. Without: 10.8 % of it gets repainted. With: 0.9 %. - The old outfit comes off. Without, old boots or jeans stay on under the new outfit (cleared in 0 of 3 seeds). With: 2 of 3. The pictures on this page show it. Yellow marks every pixel that differs from the original picture. Without the LoRA the face, the hair and the background light up. With it, only the clothes do. What it does not do It does not draw the outfit better. Buttons, belts and patterns come out the way plain Qwen Image 2.1 draws them, with or without the LoRA. Sometimes plain Qwen copies more of the outfit: in the train picture it swapped the pants too, where the LoRA kept the old jeans and belt, and in the field picture it closed and belted the coat, where the LoRA left it open. The LoRA is for the rest of the picture. It keeps the framing, the body, the face and the background where they were, so that only the clothes you can see change. What I set out to fix I made this because the outfit swap workflow I was working on messed things up about half the time, and those results were not usable. Before training anything I ran 47 swaps with plain Qwen Image 2.1 and marked every one. I liked 24. The other 23 had something wrong with them, and usually it was not the outfit itself: - the camera pulled back to fit the whole outfit in, - pants were pushed into a shot that had no legs in it (Steve Urkel style), - the body or the pose was redrawn to carry the new clothes, - or everything simply moved a few pixels. The last picture on this page shows four of those swaps, the same workflow and seed without the LoRA and with it. None of them is in the training set. What happens to the old clothes A sentence after the request steers what stays on: - Replace everything they wear. takes off old tights and legwear. - Keep their own shoes and legwear. keeps them. How to use it My has it set up: two pictures in, the outfit gets described for you, the sentence above sits in a box you can edit. In your own two-picture Qwen Image 2.1 edit graph: - A LoRA loader right after the model loader, strength 1.0. At 0.5 the picture starts to move again. - Text Encode Qwen Image 2.1: the person as image_1, the outfit as image_2, resolution 0, the request as the prompt. - KSampler on the encoder's latent output: 25 steps, CFG 1, euler / simple, denoise 1. - VAE Decode, then Split Image with Alpha (the Qwen 2.1 VAE decodes RGBA). Limits - It does not copy the outfit more exactly than plain Qwen does. Buttons and belts can be wrong either way, and a knit pattern came out flatter with the LoRA in the cafe picture. - It holds on to what was there. Old pants and a belt stayed on in one test, even with Replace everything they wear., and a coat that is closed in the outfit picture can stay open. - It holds the picture, so it holds the pose. An outfit that needs a different pose will not get one. - Shoes are the stubborn part. A pair sometimes stays on either way. - Something that lies over the clothes, like a bag strap or an earphone cable, can go with the old outfit or sit oddly on the new one. - Trained at about 1 MP, tested at about 2 MP with 25 steps and CFG 1. - With the Viggle Turbo LoRA at 8 steps it still holds the picture. Plain fabric can come out a little grainy. Training - ai-toolkit (qwen_image_2) on the Comfy-Org INT8 convrot base. Rank 32, alpha 32, AdamW8bit, learning rate 1e-4, batch 1, 1,000 steps. - 66 swap pairs. Each started as a real Qwen Image 2.1 swap. I moved it back onto the person picture by whole pixels and kept only the clothes from the swap: the face, hair, hands and background are the person picture's own pixels. I looked at every one and kept the ones I liked. The full numbers, the step 1,250 and 1,500 files and the notes on how it was made are on the . Qwen Image 2.1 is by Alibaba Qwen, under the Qwen Research License: non-commercial use only. Questions or bugs: the comments here or . Videos on . More from me on and .
2,261 downloads · 138 likes on Civitai
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4DDFEAC5695ADAED1F0F78B23FDA40919FD2ED6A4AF790CED6C1E043DC4AE1F0
Ranking badge
Updated Oct 22, 2026
Qwen Image 2.1 Outfit Swap Consistency LoRA on ModelTrends.ai: #136 Hottest AI model
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Also ranked: #2 Hottest Qwen2 model · #2 Hottest Qwen2 LoRA
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Qwen Image 2.1 Outfit Swap Consistency LoRA Popularity Trend
Heat score since 4 Oct 2026
Heat score
8,585°
This week
▲
29.8%
8,533° then, 8,585° now
This month
n/a
Wasn't released/tracked
Past year
n/a
Wasn't released/tracked
Qwen Image 2.1 Outfit Swap Consistency LoRA: Heat score since 4 Oct 20267,000°7,444°7,888°8,331°8,775°4 Oct8 Oct11 Oct15 Oct18 Oct22 Oct8,585°ModelTrends.ai
7,000°
Floor
The scale runs from 0° to 9,999°. Everything below 7,000° is kept for models no source reports on yet, which carry a stand-in number there so lists stay complete. 7,000° is where measured data begins: a model with real data but almost no downloads sits at the floor, and the measurements fill the degrees above it. The floor says nothing about the model; only the degrees above it do, and they are what separates one model from another.
+1,026°
Civitai downloads
2,261 downloads of this exact version on Civitai. Downloads are the heaviest ingredient and are counted on a log scale: ten times the downloads adds the same 300°, so a model with a million downloads is not a thousand times hotter than one with a thousand. The six download sources share that one term, split between them in proportion to their counts.
+321°
Likes
138 likes and thumbs up across the sources. A like weighs half a download, on the same log scale.
+138°
Adoption rate
About 68 downloads a day, measured between two readings of the sources, never guessed from a lifetime average. Speed weighs a quarter of the download term, so a fresh surge shows without letting a one-day spike outrank years of use.
+100°
Family boost
+100° because this is a LoRA of a family this site is nudging forward right now. It is a bounded nudge inside the score and is listed here openly; it can never hide a model or outweigh a thousandfold difference in downloads.
Show detailed breakdown
Every number on this site can be checked. This model's heat score is 8,585°, and here it is built one ingredient at a time, with the running total after each: the floor, the degrees each source adds, the bonus for the kind of model and what the age of its weights takes away. The colors are the bands of the chart above. The glossary at the end defines every term.
  1. 1
    Start at the floor.
    Why 7,000° and not zero: the scale runs from 0° to 9,999°, and the part below 7,000° is reserved for models no source reports on yet, which carry a stand-in number there so the lists stay complete and never outrank a model with data. 7,000° is where measured data begins. A model with real data but almost no downloads sits here; everything that follows is measurement, and the room above the floor holds ten tenfold steps in downloads at 300° each. The floor is the same for every model, so it decides nothing; the degrees above it do.
    7,000°
    running total
  2. 2
    Add the downloads.
    2,261 download-equivalents in all, from Civitai downloads. Ten times the downloads adds the same 300°, so size matters but never runs away with the score.
    +1,026°
    8,026°
    running total
  3. 3
    Add the likes.
    138 likes and thumbs up, at half the weight of a download.
    +321°
    8,347°
    running total
  4. 4
    Add the adoption rate.
    About 68 downloads a day right now, measured between two readings, at a quarter of the weight.
    +138°
    8,485°
    running total
  5. 5
    Family boost.
    An open, bounded nudge for LoRAs of a family this site is pushing forward right now.
    +100°
    8,585°
    running total
  6. =
    The heat score.
    Where this model stands on every list of this site. Nothing else adjusts it.
    8,585°
Glossary: the terms used here
Heat score
One number for how much a model is used and wanted right now, from 0° to 9,999°. Every list on this site that says hottest is sorted by it and nothing else.
Floor
The 7,000° every model with real data starts from. The scale runs from 0° to 9,999°; the part below the floor is reserved for stand-ins (models without data), so that a model with data always ranks above one without. The floor is the same for everyone and decides nothing; the degrees above it are the measurement.
Download-equivalents
Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
Log scale
Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
Likes
Thumbs up and likes from every source, worth half a download each on the log scale.
Adoption rate
How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
Measured and estimated
Measured means two readings of a source exist and the difference is real. Estimated means only today's total is known and the past is spread over the model's life; the site says which one it is showing.
Seeder
Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
AI Horde
A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
Generation sites
Sites that host their own copies of a model and let people generate with it, such as PixAI, SeaArt and Yodayo. Their downloads count like Civitai's and each generation run as one download.
OpenRouter tokens
A text model served through an API, such as Claude or GPT, has no weights to download, so its usage is measured in tokens: the pieces of text it read and wrote through OpenRouter, a gateway many apps use, over the last 30 days. Every 10,000,000 tokens count as one download. Source: OpenRouter (openrouter.ai/rankings), CC BY 4.0.
Full model (checkpoint)
The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
LoRA and embedding
Small add-on files that steer someone else's weights toward a style, a character or a concept. They cannot run alone.
Family and weights
The base a model is built on, such as SD 1.5, SDXL, Flux or Wan. Every model inherits the release date of its family's weights.
Age
Degrees taken off for how long ago the family's weights came out: 150° a year, up to 750°. It keeps old downloads that had years to pile up from freezing the top of the list.
Family boost
A small, bounded nudge for LoRAs of a family this site is pushing forward right now, always listed in the breakdown.
Stand-in score
A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
New! (grace period)
A model less than 7 days old shows New! instead of a score and holds no place in the rankings. Its score is computed from day one, but a model one day old grows faster than anything, so without the wait the week's #1 would always be whatever came out yesterday rather than what held up for a week.
Trend
How a model's growth over a period compares with the typical model's growth over the same period. Faster than typical reads as a rise, slower as a fall.
Typical model
The middle of the catalog: half the models with a figure grew faster over the period, half slower.
How this model's popularity has moved against the rest of the catalog: its growth in downloads, likes and usage over each period, measured against the typical model's growth over the same period, with its heat score at the time. Above the typical growth reads as a rise, below it as a fall. The past is reconstructed from today's totals, the model's first day and its measured download speed where two readings exist; a model that did not exist at the start of a period shows n/a.
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qwen-image-2.1-outfit-swap.safetensors
152 MB · SafeTensor · bf16
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