Deepfake Generator
A deepfake generator that runs in your browser — thirteen swap models, 1024px output, photo and video on one pipeline, a render back in about a minute.
A deepfake generator is the part of the stack that does the real work: it locates a face in your target file, rebuilds it carrying the identity from a source image, and composites the result back into the frame. The upload box and the progress bar are packaging. What decides whether the file you download is usable is the deepfake generator underneath — which models it runs, what resolution it swaps at, how it handles occlusion, and how long a job takes.
The deepfake generator on this page is built on FaceFusion 3.6.1, so it is not one black box with a quality slider. Thirteen swap models sit behind the same button, each biased differently toward identity strength, skin fidelity or edge softness, and each can be pixel-boosted to 1024×1024 before compositing. The defaults are tuned so most people never open the advanced panel, which is there for the shots that need it.
Nothing installs and you do not need a GPU. Files upload straight to storage, the job runs on our hardware, and the render comes back to the tab you started in. An image job costs ten credits and a video job thirty, and new accounts start with a balance, so you can test this deepfake generator on your own footage before thinking about a plan.
What This Deepfake Generator Actually Runs
Thirteen swap models, one button
Inswapper, SimSwap, Ghost, HyperSwap, BlendSwap, UniFace and HiFiFace all ship inside the same deepfake generator, and the default routes most jobs to whichever holds identity best at your input size. Changing model is a dropdown, not a reinstall, so a shot that resists one architecture can be re-rendered on another.
Pixel boost up to 1024×1024
Most swap models are trained at 128 or 256 pixels, which is why cheap output goes soft the moment a face fills the frame. This deepfake generator adds a pixel-boost pass that rebuilds the swapped region at up to 1024×1024 before compositing, so a close-up keeps skin texture instead of a smooth mask.
Photo and video on one pipeline
Stills up to 10 MB and video up to 100 MB go through the same deepfake generator, with per-frame tracking so a swapped face does not flicker or drift when the head turns. A video job gets fifteen minutes of processing, which covers most short-form footage at full frame rate.
Face and frame enhancement built in
CodeFormer, GFPGAN and GPEN restore facial detail after the swap; Real-ESRGAN and its siblings upscale the whole frame at 2×, 4× or 8×. Both are toggles rather than separate products, so the deepfake generator returns a cleaned, upscaled file in one pass instead of three round trips.
Detection, landmarks and occlusion control
RetinaFace, SCRFD, YOLO-Face and YuNet are all available as detectors, with rotation angles for sideways footage and XSeg masks for hands, microphones or hair crossing the face. When a frame holds several people, selector order and gender filters decide who gets swapped; everyone else takes the deepfake generator defaults.
How to Use the Deepfake Generator
Upload the target
Drop in the photo or clip you want the face to land in — up to 10 MB for an image, 100 MB for video. The deepfake generator reads the frame and finds every face in it first.
Add the source face
Upload a reference image of the face you want mapped in, or open a dedicated page where the source is already locked. Front-lit, straight-on references give the deepfake generator the most geometry to work from.
Render and download
Start the job. A photo comes back in well under a minute, a clip in proportion to its length, and the deepfake generator returns the file at the resolution you supplied.
Three steps is the whole flow. Everything past that — model choice, pixel boost, enhancers, occlusion masks — lives in the deepfake generator's advanced panel and is optional.
What People Run Through the Deepfake Generator
A deepfake generator is a format, not a purpose. These are the jobs that come through most often, and every one stays inside the consent rules further down this page.
Meme and reaction edits
The oldest joke on the internet still works, and a deepfake generator turns the punchline into a sixty-second job rather than an evening in a photo editor — which matters when the reference expires tomorrow.
Short-form video and thumbnails
Creators cutting for vertical feeds use a deepfake generator to keep a running visual gag consistent across a series, and for thumbnails that would otherwise need a licensed press shot.
Previs and casting boards
Directors put a rough render in front of a room to show what a role looks like with a particular face in it, long before a camera is booked. Deepfake generator output is good enough to judge from.
Dubbing and localisation mockups
Studios preview how a scene reads with a different performer before committing to a re-shoot, using a deepfake generator for the mockup rather than for anything that ships.
Detection research and training
Trust-and-safety teams, journalists and students have to see the artefacts before they can spot them. Reading a deepfake generator's output for where it breaks teaches more in an hour than a week of papers.
How the Deepfake Generator Works, Step by Step
From upload to download: the actual pipeline
The first thing a deepfake generator does is detection. RetinaFace or YOLO-Face scans the frame at 640×640 and returns a box for every face it finds; on rotated footage, a detector angle of 90 or 270 degrees stops it missing the face entirely. Landmarking follows, placing dozens of points on the eyes, nose, mouth and jaw. Those points let the aligner warp the face into a canonical square, and they are why a heavy fringe or a hand across the chin costs quality: landmarks the deepfake generator cannot see are landmarks it invents.
Only then does the swap happen, inside that aligned square. The swapper takes the identity embedding from your source image and rebuilds the target face carrying it, at whatever pixel-boost resolution you asked for. The result is warped back into the frame, feathered against an occlusion mask so anything crossing the face stays in front of it, then handed to the enhancers. That order explains most quality complaints: a bad detection ruins everything downstream and no enhancer recovers it. When a deepfake generator result looks wrong, work backwards along the chain.
Picking a model and a pixel-boost setting
Inswapper is the default for good reasons — it holds identity well, it is fast, and its fp16 variant halves memory cost with no visible loss. SimSwap gives softer, more forgiving blends and is the fallback when target lighting sits far from the source. Ghost and HyperSwap keep fine structure such as eyelids and lip borders more faithfully, at some cost in speed. BlendSwap leans toward the target's own skin tone. No model wins everywhere, which is why this deepfake generator exposes all of them.
Pixel boost is a separate decision. A 256-pixel model asked to fill a 1024-pixel face looks soft; boosting rebuilds that region at higher resolution before compositing. Match the boost to how large the face sits in your frame: a head occupying a tenth of a 1080p frame gains nothing from 1024×1024 and costs render time, while a head filling a 4K frame needs it. The deepfake generator lets you set either.
What actually decides how long a render takes
Throughput on a deepfake generator is almost entirely a function of frame count, not file size. A photograph is one pass through the pipeline and finishes well under a minute. A ten-second clip at thirty frames per second is three hundred passes plus the tracking that keeps identity stable between them, which is why video jobs get fifteen minutes of wall clock. A 100 MB locked-off shot often processes faster than a 20 MB fast pan, which forces the detector to re-acquire the face on almost every frame.
The other lever is the enhancer stack. Face enhancement adds a fixed cost per detected face per frame; frame enhancement at 4× or 8× runs on the entire image and is by a wide margin the most expensive stage in the deepfake generator. If a job feels slow, switching frame enhancement off and upscaling afterwards is faster. Credits follow the same logic — ten for an image, thirty for a video — because the video path does strictly more work.
Getting a Cleaner Render
Most disappointing output traces back to input rather than to the engine. A deepfake generator cannot recover detail that was never captured, so upscaling a small thumbnail before uploading only hands the detector more blurry pixels. Start from the largest original you hold; if all you have is a screenshot, expect a softer render and plan the crop around it.
The second recurring problem is mismatch between source and target: head angle, lighting direction and expression. Faces carry emotion in the mouth and the eye corners, and a neutral source dropped onto a wide laugh forces the model to stretch geometry it does not have. Keep the two within thirty degrees of pose and in the same expressive family and the deepfake generator needs far less cleanup.
- Upload the largest original you have, never a re-saved screenshot
- Keep the face large in frame — a distant subject gives the detector nothing
- Match pixel boost to face size instead of always maximising it
- Enable the occlusion mask when hands, hair or a mic cross the face
- Try a second swap model before blaming the deepfake generator for a soft render
- Check hairline, eyes, teeth and neck seam before you publish
Consent and Responsible Use
Every render from this deepfake generator is bound by one hard rule: no sexual or pornographic content, ever. It is filtered at the model level, enforced on the account, and no plan, setting or advanced option in the deepfake generator changes it — accounts that try lose access permanently. That is not a disclaimer buried at the foot of a page, it is the line the product is built around.
The second rule is about presentation. A deepfake generator output shared as an obvious edit is satire, commentary or fan work, and all three are legitimate. The same file passed off as authentic footage is deception, and in a growing number of jurisdictions it is also a crime: several countries and a majority of US states now prosecute non-consensual synthetic media, and disclosure laws for political and commercial use are spreading fast. Label your work, get a likeness release before commercial use, and never publish a render of a real person doing something they never did.
Deepfake Generator FAQ
Is this deepfake generator free to use?
There is a free tier. New accounts start with a credit balance, so you can render without paying or installing anything. Paid plans buy throughput, longer clips, priority processing and removal of the aideepfake.io mark, but the deepfake generator itself is open to everyone.
What files can I upload?
Images up to 10 MB and video up to 100 MB, in the usual web formats. The deepfake generator takes a still or a clip as the target and a still image as the source face; the two need not match in resolution or aspect ratio.
What resolution does the swap run at?
Up to 1024×1024 with pixel boost enabled, and the composited output keeps whatever resolution you uploaded. A deepfake generator that only swaps at 128 pixels always looks soft on a close-up — the boost pass is what avoids it.
How long does a render take?
A photo is usually back in well under a minute. Video scales with frame count rather than file size, and a job gets fifteen minutes before it times out. Frame enhancement at 4× or 8× is the slowest stage in the deepfake generator by a wide margin.
What happens to the files I upload?
They are used to produce your render and nothing else — not added to training data, not resold, not published to any gallery. Whatever you put into the deepfake generator stays yours.
Can I make explicit or pornographic content?
No. Sexual deepfake content is banned outright, filtered at the model level, and grounds for permanent loss of access. No plan, setting or advanced option in the deepfake generator unlocks it, and reports are acted on.
Is using a deepfake generator legal?
It depends entirely on what you do with the output. Parody, commentary, research and clearly labelled fan work are broadly protected in most jurisdictions. Passing a deepfake generator render off as real footage, using a real likeness commercially without a release, or producing sexual material is not — a growing number of countries and US states prosecute it.
Related Tools
The same deepfake generator engine, pointed at a different starting point.
Open the Deepfake Generator
Upload a photo or a clip, pick a face, and let the deepfake generator hand the render back before your coffee cools.
Start rendering