How to Face Swap a Video Online: Step-by-Step Guide (2026)

Video face swap replaces a person's face in a video with a face from a single photo, frame by frame, while keeping the original motion, lighting, and expressions intact. NamiFusion's online video face swap tool runs entirely in the browser: upload up to 8 videos at once, map one or several source faces, and download clean, watermark-free results. New accounts get free credits at signup, and paid usage runs on a simple system where $1 buys 100 credits.

TL;DR

Batch up to 8 videos in one run and swap faces across all of them at once.

Two modes: single-face (one source face per video) or multi-face (map every detected face individually).

Cross-video deduplication means the same person only needs to be mapped once, even across multiple clips.

Failed clips can be retried individually, and finished videos land in a history strip right on the page.

Pricing starts free: signup credits cover your first swaps, then $1 = 100 credits with no subscription required.

How do you swap faces in a video online?

1. Open the video face swap tool on NamiFusion and sign in — new accounts receive free credits automatically.

2. Upload your target videos. You can drag in up to 8 clips at once for batch processing.

3. Pick a mode: single-face if each video only needs one face replaced, or multi-face to map several faces individually.

4. Upload the source face photo(s). A sharp, front-facing photo with even lighting gives the best results.

5. If the same person appears in several videos, map them once — cross-video deduplication applies that mapping everywhere.

6. Optionally adjust the detection frame count for footage with fast motion or many people in frame.

7. Start the swap and watch per-clip progress. Finished videos appear in the history strip on the same page.

8. Preview and download your results, and retry any individual clip that failed — no need to rerun the whole batch.

Single-face vs multi-face mode: which should you use?

Single-face mode is the fast path: you provide one source face per video and NamiFusion swaps it onto the face detected in that clip. It is ideal for talking-head videos, short-form content, and memes where only one person matters. In my experience it covers the vast majority of everyday swaps.

Multi-face mode detects every face in your footage and lets you map each one to a different source photo. Use it for group scenes, dialogues, or music videos. Each detected face gets its own mapping slot, so you always know exactly who becomes whom — and thanks to deduplication, a person who shows up in clip one and clip five still only needs a single mapping.

What can you use video face swap for?

Creators use video face swap for meme edits and reaction content, filmmakers use it to previsualize casting choices or fix a scene without a reshoot, and marketers localize one ad with different presenters for different markets. Batch mode is what makes the last two practical — you upload all the variants at once instead of babysitting clips one by one.

Because NamiFusion is unfiltered, it also serves creators whose content mainstream tools reject. Whatever your use case, the same rule applies: only swap faces you have the right to use.

How much does it cost to face swap a video?

NamiFusion runs on credits: $1 buys 100 credits, and every new account starts with free signup credits, so you can test video face swap without entering a card.

Cost scales with the footage you process: each clip in a batch runs as its own job, so a short meme costs less than a long scene, and a failed clip can be retried on its own instead of paying for the entire batch again.

If you plan to run swaps at scale, the same models are exposed through the API marketplace, where every model card shows an approximate dollar price per video — handy for estimating a budget before you commit.

How do you get the most realistic result?

The source photo matters more than anything else. Use a sharp, front-facing shot with even lighting, no sunglasses, and only one face in the frame. A good source photo fixes more problems than any setting will.

On the video side, footage where the face is reasonably large in frame and not constantly motion-blurred swaps far better. For fast cuts or busy scenes, raising the detection frame count helps the tool track every face reliably.

Finally, iterate cheaply: run one clip first, check it in the history strip, and only then launch the full batch. If a single result disappoints, retry just that clip with a different source photo.

Can you automate video face swap with an API?

Yes. The web tool is backed by NamiFusion's model marketplace, which exposes 98+ models through one unified REST API. Create a key on the /api-keys page, POST your job to the run endpoint, then poll the task until it completes.

Before writing any code, you can test the exact model in the marketplace Playground for free and check its per-video price on the model card.

curl -X POST "https://www.namifusion.com/api/v1/marketplace/run/<model_id>" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": {
      "video_url": "https://example.com/clip.mp4",
      "face_image_url": "https://example.com/face.jpg"
    }
  }'

# Poll until the task completes
curl "https://www.namifusion.com/api/v1/marketplace/run/tasks/<task_uuid>" \
  -H "Authorization: Bearer YOUR_API_KEY"