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Disguise Drop LTX 2 / Wan2.1 14B FLF2V

7927°
Disguise Drop   LTX 2 / Wan2.1 14B FLF2V
Created by
kabachuha
on Civitai
by kabachuha - Disguise Drop - LTX-2 / Wan2.1 14B FLF2V
Creator notes
When the mask falls off… who’s really inside? LTX-2 Disguise Drop! Remake of my very first Wan lora now for LTX-2! The sound effects take it to a new level! The LoRA brings the classic unzipping surprise cartoon effect where a character suddenly unzips their skin, revealing another character inside them all along! This time - compared to my other LTX-2 loras so far - thanks to calibrated LR scheduling, it has virtually no grayness and you can use it in image2video and first-last-frame2video modes alike! The workflows are embedded within the videos or you can use the .json file inside the Huggingface files folder at . It's the native workflow with KJ Nodes and VideoHelperSuite. The training recipe is exactly the same as for my previous one-hand-squish lora, except for the lowered rank to prevent overfitting. This lora converged in 3520 steps. The model was trained with Disguise drop. as the prefix, but you can simply describe the action in details. Wan 2.1 This Wan2.1 First-last-frame LoRA aims to replicate the weird cartoonish transformation effect of full-body disguise, where it turns out that another person or a cartoon character has been inside the source person all along (or vice versa) when the first person unzips their skin. This lora is tested to run in kijai's Wan Wrapper nodes + ComfyUI essentials for histogram correction of 0.2 (otherwise the frames will be too dark), with the default lora weight of 1.0. The LoRA has been trained using diffusion-pipe for 70 epoch with variable flow shift: 4.3 (for ~ 40 epochs) -> 3.9 to capture both macroscopic changes (the falling skin) first and then the exact hand movements, using Prodigy optimizer. The train resolutions are 688x688x49 and 688x688x65. As the text encoder is not trained, the keywords have little effect, and I recommend describing the action in details following the prompt-template below: """ The video begins with [object]. [She/He] touches the top of [her/his] head with [her/his] hand and then [she/he] fully unzips [her/his] skin in two halves slowly pulling the zip with [her/his] hand across [her/his] body from the top of [her/his] head, splitting [her/his] face, to the waist to reveal [target object] inside [her/him]. The [target object] then throws away the previous skin. """ The ending sentence variation is "The previous skin then falls down", if you don't want to toss it around. Also, you can have the same pictures at the beginning and the end resulting in an endless loop of unpeeling :) This is an experimental lora and the success rate varies! The model sometimes tries to cheat using a "bag" to put the subject into for later unzipping. For the time being, add "bag, shell, case, hood, zipper, cloth, grainy, dark, movie shot, old movie, jungle, vegetation, plants" to the negative prompt. Obviously, the lora works the best when the subjects share the same or at least a similar background.
813 downloads · 95 likes on Civitai
SHA256
E824840D740E6D14350A5336EB7AF720F73EA80A3EE9EC578946701785D2CD33
Ranking badge
Updated Oct 22, 2026
Disguise Drop LTX 2 / Wan2.1 14B FLF2V on ModelTrends.ai: #50 Hottest Wan LoRA
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Also ranked: #59 Hottest Wan model
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Disguise Drop LTX 2 / Wan2.1 14B FLF2V Popularity Trend
Heat score, last 12 months
Heat score
7,927°
This week
n/a
Wasn't released/tracked
This month
n/a
Wasn't released/tracked
Past year
n/a
Wasn't released/tracked
Disguise Drop LTX 2 / Wan2.1 14B FLF2V: Heat score, last 12 months7,000°7,332°7,664°7,995°8,327°Oct 2025Dec 2025Mar 2026May 2026Aug 2026Oct 20267,927°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.
+879°
Civitai downloads
813 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.
+297°
Likes
95 likes and thumbs up across the sources. A like weighs half a download, on the same log scale.
+9°
Adoption rate
About 0 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.
−258°
Age
−258° because the Wan weights came out in 2025. Every model inherits the age of the weights it is built on: 150° a year, up to 750°, and it keeps growing until then. Without it the top of the list would be 2022 and 2023 checkpoints on the strength of downloads that had years to pile up.
Show detailed breakdown
Every number on this site can be checked. This model's heat score is 7,927°, 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.
    813 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.
    +879°
    7,879°
    running total
  3. 3
    Add the likes.
    95 likes and thumbs up, at half the weight of a download.
    +297°
    8,176°
    running total
  4. 4
    Add the adoption rate.
    About 0 downloads a day right now, measured between two readings, at a quarter of the weight.
    +9°
    8,185°
    running total
  5. 5
    Take off the age.
    The Wan weights came out in 2025: 150° a year, up to 750°, growing until then.
    −258°
    7,927°
    running total
  6. =
    The heat score.
    Where this model stands on every list of this site. Nothing else adjusts it.
    7,927°
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.
Example renders
Prompts and settings shared by the people who made these renders on Civitai. Pick a render to see how it was made.
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Example render 8
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Render by kaywon53535 on
Civitai
·
Prompt on BunchaPrompts
Flag
Settings
Sampler
UniPC
Steps
6
Guidance
1
Size
480x600
Prompt
The video begins with her. she touches the top of her head with her hand and then she fully unzips her skin in two halves slowly pulling the zip with her hand across her body from the top of he head, splitting her face, to the waist to reveal real her inside her . The her then throws away the previous skin.
Render by kabachuha on
Civitai
·
Prompt on BunchaPrompts
Flag
Settings
Sampler
UniPC
Steps
30
Guidance
5
Seed
423438869217466
Size
688x688
Prompt
The video begins with an anime girl. She touches the top of her head with her hand and then she fully unzips her skin in two halves slowly pulling the zip with her hand across her body from the top of her head, splitting her face, to the waist to reveal another anime girl inside her. The new anime girl then throws away the previous skin.
Negative prompt
bag, shell, case, hood, zipper, cloth, grainy, dark, movie shot, old movie, jungle, vegetation, plants, 色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走
Render by Carpethop on
Civitai
·
Prompt on BunchaPrompts
Flag
Settings
Size
592x880
Prompt
The video begins with a bearded man in black t-shirt and black jeans. He touches the top of his head with his hand and then he fully unzips her skin in two halves slowly pulling the zip with his hand across his body from the top of his head, splitting his face, to the waist to reveal an anime girl inside him. The anime girl then throws away the previous skin and start dancing.
Settings
Sampler
UniPC
Steps
30
Guidance
5
Seed
937555909045753
Size
688x688
Prompt
The video begins with an anime girl. She touches the top of her head with her hand and then she fully unzips her skin in two halves slowly pulling the zip with her hand across her body from the top of her head, splitting her face, to the waist to reveal another anime girl inside her. The new anime girl then throws away the previous skin.
Negative prompt
bag, shell, case, hood, zipper, cloth, grainy, dark, movie shot, old movie, jungle, vegetation, plants, 色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走
Settings
Sampler
UniPC
Steps
30
Guidance
5
Seed
656542287548958
Size
688x688
Prompt
The video begins with an anime girl. She touches the top of her head with her hand and then she fully unzips her skin in two halves slowly pulling the zip with her hand across her body from the top of her head, splitting her face, to the waist to reveal another anime girl inside her. The new anime girl then throws away the previous skin.
Negative prompt
bag, shell, case, hood, zipper, cloth, grainy, dark, movie shot, old movie, jungle, vegetation, plants, 色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走
Settings
Sampler
UniPC
Steps
6
Size
1024x1536
Prompt
The video begins with a beautiful woman. She touches the top of her head with her hand and then she fully unzips her skin in two halves slowly pulling the zip with her hand across her body from the top of her head, splitting her face, to the waist to reveal a female terminator inside her. The terminator is composed of a metal skeleton. The terminator then throws away the previous skin.
Negative prompt
bad quality video,lowres,bad anatomy,bad hands,error,missing fingers,extra digit,fewer digits,cropped,worst quality,low quality,normal quality,jpeg artifacts,ugly,deformed,noisy,low contrast,sterile,untextured,extra_arms, extra
Settings
Size
832x1152
Prompt
Unzip blablablá
Settings
Sampler
UniPC
Steps
30
Guidance
5
Seed
877093430805163
Size
688x688
Prompt
The video begins with a realistic bodybuilder man flexing his muscles. He touches the top of his head with his hand and then he fully unzips her skin in two halves slowly pulling the zip with his hand across his body from the top of his head, splitting his face, to the waist to reveal a cartoon pig inside him. The pig then throws away the previous skin.
Negative prompt
bag, shell, case, hood, zipper, cloth, grainy, dark, movie shot, old movie, jungle, vegetation, plants, 色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走
Run Locally
disguise_drop.safetensors
343 MB · SafeTensor
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