5 AI face-swap software options: online, API and local

No provider is best on every source. Test the same rights-cleared face and target, then judge identity, boundary artifacts, occlusion, expression, frame stability, usable export and total effort.

Magic Hour publishes this guide and includes its own product in the comparison. Treat the recommendations as editorial guidance from a vendor, and verify the linked first-party product details and your own output requirements before choosing a tool.

Face-swap software comparison

Sources and product routes were checked September 13, 2026. Provider plans, guest limits and model behavior change; confirm the live input, export and commercial-use terms before a project.

1. Magic Hour: browser photo, GIF and video face swap

Magic Hour Face Swap runs in a browser and separates photo, GIF and video workflows. Its current FAQ documents guest access for five photo swaps and three video and GIF swaps per day. Photo guest exports are watermark-free; guest video and GIF exports include a watermark.

Magic Hour input workflow, captured September 25, 2026. This shows the upload or prompt controls, not a completed generation. View official source

Magic Hour input workflow, captured September 25, 2026. This shows the upload or prompt controls, not a completed generation. View official source

The dashboard supports individual face mapping for footage with multiple people, and the video route accepts an upload or YouTube URL. Developers can use the photo face-swap API and store the returned project ID for status and downloads.

• Best for: a fast browser evaluation, multi-format creative workflow or API-backed product.

• Check: source-face clarity, selected face mapping, video frame stability, current credit quote and commercial-use terms.

• Constraint: photo and video have different guest limits, credit behavior and output conditions.

2. Remaker: quick single-, multi-face and batch routes

Remaker’s photo tool exposes single-face, multiple-face and batch options. Its video face-swap route accepts video or GIF/WEBP input and provides separate single- and multi-face paths.

This makes Remaker relevant for users who want a simple browser workflow or need to process several still images. Treat each route as a separate product: check the current credit rule, file cap, output condition and privacy policy before uploading sensitive material.

3. Akool: broader swap types and API workflows

Akool’s current swap studio covers face, head, character and motion swap. Its face-swap workflow accepts images and video, detects faces, and lets the user assign a replacement. Akool also maintains an API surface for teams.

Choose Akool when the project may expand beyond a simple face replacement. Its wider toolkit also means you should confirm which swap type, model and account tier produces the intended result rather than treating every mode as equivalent.

4. FaceFusion: current local and batch operation

FaceFusion is the current local option in this list. Its documentation exposes interactive, headless and batch modes, and processors including face swap, face enhancement, expression restoration and lip sync.

The installation guide requires Python, Conda and a supported runtime. Local execution can improve control over processing and storage, but it does not remove the need for consent, secure files or output review. Hardware and configuration affect speed and results.

5. DeepFaceLab: legacy training-based workflow

DeepFaceLab’s original repository uses an extract, train and merge workflow and offers detailed local control. GitHub shows that the owner archived it on November 13, 2024, making it read-only.

Keep it only when you already understand and maintain that workflow. For a new local setup, evaluate FaceFusion first. Do not repeat old claims that DeepFaceLab is automatically “cinema quality”; output depends on source data, training, hardware, compositing and review.

How to run a fair face-swap test

• Use one source face. Choose a sharp, rights-cleared image with neutral expression and unobstructed features.

• Use three targets. Test a front-facing still, a three-quarter angle and a short moving clip with one occlusion.

• Keep the task constant. Do not compare a still-image result from one tool with a complex video from another.

• Review at full size. Inspect eyes, teeth, hairline, ears, skin boundary, lighting, expression and every difficult video frame.

• Record total cost. Include rejected attempts, watermarks, required enhancement, setup time, download limits and human repair.

Which option should you choose?

• Fast browser test: Magic Hour or Remaker.

• Multiple swap types or a team/API path: compare Magic Hour and Akool with your exact inputs.

• Local, current, configurable workflow: FaceFusion.

• Existing training-based pipeline: DeepFaceLab only if you already maintain it and accept the archived upstream repository.

Consent, disclosure and commercial use

Use faces and footage you own or have permission to edit. Do not create deceptive impersonation, non-consensual sexual content, fraud or false endorsements. Keep the original, permissions and edit history, and label synthetic media when the platform, audience or context requires it.

A tool allowing a file upload does not grant rights to the person, character, footage, music or brand in that file. Recheck the provider’s current terms and the distribution platform’s rules for commercial work.