AI porn models for adult image and video generation
Browse the building blocks behind the factory. Filter checkpoints and LoRAs by image or video support, base model, and tags, then open any version directly in the unified generator.
Instagramification
The Instagramification LoRA creates images of women resembling Instagram influencers. It enhances features like lips, skin tone, hair, and makeup, often adding large breasts, based on datasets from popular Instagram Baddies LoRAs and trained on Wan2.1-T2V-14B, working for both text-to-video (T2V) and image-to-video (I2V) applications.
Wan NSFW Posing Nude
This model generates NSFW nude portraits of standing, posing figures, focusing on anatomical accuracy and physics in a photoshoot setting. It was trained on a dataset designed to minimize bias toward specific facial features or accessories, allowing users to control details via prompts. It works best with specific aspect ratios and benefits from the use of lightning LoRAs for efficient generation.
WAN DR34ML4Y - All-In-One NSFW
WAN DR34ML4Y is an all-in-one NSFW LoRA model designed to handle various specific concepts like double blowjobs, missionary position, reverse cowgirl, and doggy style. It accurately generates images based on specified keywords and positions. It is recommended to use both models to produce ideal outputs.
Wan 2.2 / 2.1 - Anal Reverse Cowgirl POV - t2v - i2v
Wan 2.2/2.1 is a text-to-video and image-to-video model trained on realistic videos. It generates high-quality animations, including depictions of sexual acts like anal sex, based on text prompts. Version 2.1 is compatible with both I2V and T2V models, trained using diffusion-pipe.
WAN DR34MJOB - Double/Single/Handy Blowjob
WAN DR34MJOB is a LoRA model designed to generate images of single and double blowjobs, including POV shots. It also produces images of handjobs. Using the specified triggers is necessary for desired outputs.
WAN 2.2 I2V - Combo Handjob Blowjob
This model generates images of a woman performing simultaneous hand and mouth stimulation. It works well at strength 1, supporting both POV and third-person perspectives, and is best suited for live-action images due to potential blurring on animated fingers. The model was trained to prioritize image quality over smaller file size.
Wan POV Doggy Style (i2v)
This model is trained for image-to-video generation of doggy style scenes, specifically optimized for vertical videos and using the trigger word "POVdog." Version 1.1 provides consistent motion for the doggy style position, with emphasis on ass movement and bounce, although it may have image artifacts due to the low resolution source video data. The model reportedly works well in conjunction with aipinups69's Wan 2.1 LoRA at a strength of 0.5.
(wan 2.2 experimental) WAN General NSFW model
Explore available lora versions and generation modes.
Ahegao Face Wan (i2v)
This LoRA model generates ahegao faces, typically including drool and tongue protrusion. It was trained on a small dataset of videos and images and may sometimes produce sharp, vampire-like teeth. Users can try mitigating this by adding "sharp teeth" and "vampire teeth" to the negative prompt.
How checkpoints and LoRAs fit together
Start with a checkpoint
A checkpoint controls the base rendering system. Its supported modes determine whether it can create images, edit an input, or produce video.
Match the base model
A LoRA must target the same base-model family as the checkpoint. Similar names do not guarantee compatible weights.
Check the validated workflows
A catalog version can be documented before it is generator-ready. Only versions with validated broker and artifact mappings can spend credits.