Deepfake AI
A deepfake AI tool that runs entirely online — thirteen swap models, 1024px output, photo and video through one pipeline, and a finished render back in about a minute.
- A clear, front-facing photo of one person
- Logos, landscapes and text screenshots will not work
Deepfake AI is the family of neural networks that can take a face from one image and rebuild it inside another photo or video, keeping the target's pose, lighting and expression while carrying the source's identity. The term covers everything from research code on GitHub to one-click apps, and the gap between them is enormous. What separates a usable deepfake AI from a novelty filter is the machinery underneath: which swap models it runs, what resolution it rebuilds the face at, how it tracks a face across video frames, and how it handles hair or hands crossing the jawline.
The deepfake AI on this page is built on FaceFusion 3.6.1, the most actively developed open face-swap stack, wrapped in a browser tool so none of that machinery has to be installed. Thirteen swap models — Inswapper, SimSwap, Ghost, HyperSwap, BlendSwap, UniFace and HiFiFace among them — sit behind one button, and each can be pixel-boosted to 1024×1024 before the result is composited back into your frame. The defaults are tuned so most jobs never need the advanced panel, which stays available for the shots that do.
Everything runs online: files upload straight to storage, the job renders on our GPUs, and the download lands back in the tab you started from. An image job costs fifteen credits, a video job twenty, and every new account gets twenty credits free at signup — enough to run this deepfake AI on your own footage once before deciding whether it earns a plan. No GPU, no Python environment, no gigabytes of model weights on your disk.
What This Deepfake AI Actually Runs
Thirteen swap models behind one button
Inswapper, SimSwap, Ghost, HyperSwap, BlendSwap, UniFace and HiFiFace all ship inside the same deepfake AI, each biased differently toward identity strength, skin fidelity or edge softness. The default routes most jobs well, and switching architecture is a dropdown rather than a reinstall, so a stubborn shot can be re-rendered on a different model in seconds.
Pixel boost up to 1024×1024
Most face-swap networks are trained at 128 or 256 pixels, which is why free deepfake AI output so often turns to plastic the moment a face fills the frame. This tool adds a pixel-boost pass that rebuilds the swapped region at up to 1024×1024 before compositing, so a close-up keeps pores and skin texture instead of a smooth mask.
Photo and video on one pipeline
Stills up to 10 MB and clips up to 100 MB go through the same deepfake AI engine, with per-frame tracking so the swapped face holds steady when the head turns instead of flickering between frames. A video job gets fifteen minutes of processing, which covers most short-form footage at full frame rate.
Enhancement built into the render
CodeFormer, GFPGAN and GPEN restore facial detail after the swap; Real-ESRGAN upscales the whole frame at 2×, 4× or 8×. Both are toggles inside the same job, so the deepfake AI hands back a cleaned, upscaled file in one pass instead of sending you through three separate tools.
Detection and occlusion control
RetinaFace, SCRFD, YOLO-Face and YuNet are all available as face detectors, with rotation angles for sideways footage and occlusion masks for hands, microphones or hair crossing the face. In a frame with several people, selector order and gender filters decide who gets swapped — control that most online deepfake AI generators simply do not expose.
How to Use the Deepfake AI
Upload the target
Drop in the photo or clip you want the new face to land in — up to 10 MB for an image, 100 MB for video. The deepfake AI scans the frame and locates every face in it before anything else happens.
Add the source face
Upload one clear reference image of the face you want mapped in. Front-lit, straight-on references give the AI the most facial geometry to work from, and one good photo beats five mediocre ones.
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 AI returns the file at the resolution you supplied.
Three steps is the whole flow. Everything beyond that — model choice, pixel boost, enhancers, occlusion masks — lives in the deepfake AI's advanced panel and is entirely optional.
What People Make with Deepfake AI
Deepfake AI is a capability, not a purpose. These are the jobs that come through this tool most often, and every one of them stays inside the consent rules further down the page.
Memes and reaction edits
The internet's oldest running joke, compressed from an evening in a photo editor into a sixty-second deepfake AI job — which matters when the format you are riffing on will be stale by tomorrow.
Short-form video and thumbnails
Creators cutting for vertical feeds use AI deepfake renders to keep a recurring visual gag consistent across a series, and to build thumbnails that would otherwise need a licensed press shot or a studio afternoon.
Previs and casting boards
Directors drop a rough deepfake AI render in front of a room to show what a role reads like with a specific face in it, long before a camera or an actor is booked. The output is good enough to make the decision from.
Dubbing and localisation mockups
Studios preview how a scene lands with a different performer before committing budget to a re-shoot, using deepfake AI for the internal mockup rather than for anything that ships to an audience.
Detection research and media literacy
Trust-and-safety teams, journalists and students need to see synthetic artefacts before they can spot them in the wild. Studying where a deepfake AI render breaks — hairlines, teeth, ear geometry — teaches more in an hour than a week of papers.
How Deepfake AI Works, Step by Step
From upload to download: the actual pipeline
The first thing any deepfake AI does is detection. RetinaFace or YOLO-Face scans the frame at 640×640 and returns a bounding box for every face; on rotated footage, a detector angle of 90 or 270 degrees keeps it from 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 AI cannot see are landmarks it has to invent.
Only then does the swap happen, inside that aligned square. The swapper takes an identity embedding computed 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 ordering explains most quality complaints about deepfake AI: a bad detection poisons everything downstream, and no enhancer recovers it. When a render looks wrong, work backwards along the chain.
Choosing 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 the target's lighting sits far from the source. Ghost and HyperSwap preserve 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 single model wins everywhere, which is why this deepfake AI exposes all of them instead of hiding one behind a quality slider.
Pixel boost is a separate decision from the model. A 256-pixel network 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 only costs render time, while a head filling a 4K frame genuinely needs it. The deepfake AI lets you set either without touching anything else.
What actually decides how long a render takes
Throughput in deepfake AI 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 renders faster than a 20 MB fast pan, because the pan 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 whole deepfake AI pipeline. If a job feels slow, switch frame enhancement off and upscale afterwards. Credits follow the same logic — fifteen for an image, twenty for a video — because the video path does strictly more work.
Getting a Cleaner Render
Most disappointing deepfake AI output traces back to the input rather than the engine. No AI can recover detail that was never captured, so upscaling a tiny thumbnail before uploading only hands the detector more blurry pixels to misread. 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 deepfake AI to stretch geometry it does not have. Keep the two faces within thirty degrees of pose and in the same expressive family, and the render 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 AI for a soft render
- Check hairline, eyes, teeth and neck seam before you publish
Consent and Responsible Use
Every render from this deepfake AI 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 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 AI render 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 deepfake use are spreading fast. Label your work, get a likeness release before any commercial use, and never publish a render of a real person doing something they never did.
Deepfake AI FAQ
Is this deepfake AI free?
There is a genuine free tier. Every new account gets 20 credits once, at signup, which covers one image swap at 15 credits or one video job at 20 — full resolution, on the same models paying customers use. There is no daily refill. Paid plans buy throughput, longer clips, priority processing and removal of the aideepfake.io mark, but the deepfake AI itself is open to everyone.
Does the deepfake AI work online, or do I install something?
Entirely online. The models run on our GPUs, so there is no download, no Python setup and no hardware requirement on your side — a phone browser works. You upload, the deepfake AI renders, and the file comes back to the same tab.
What files can I upload?
Images up to 10 MB and video up to 100 MB, in the usual web formats. The deepfake AI takes a still or a clip as the target and one 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 AI that only swaps at 128 pixels always looks soft on a close-up — the boost pass is what avoids that.
What happens to the files I upload?
They are used to produce your render and nothing else — never added to training data, never resold, never published to any gallery. Whatever you put into the deepfake AI 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 AI unlocks it, and reports are acted on.
Is deepfake AI legal to use?
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 an AI deepfake 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 AI engine, pointed at a different starting point.
Try the Deepfake AI
Upload a photo or a clip, pick a face, and let the deepfake AI hand the render back before your coffee cools.
Start rendering