Local, open-source AI avatars & video face swapping
FaceSwap is an open-source desktop app for training and applying face-swapping models locally. It is best for technical users-researchers, VFX artists, and hobbyists-with a dedicated GPU who need fully controllable, non-cloud face-swap workflows. FaceSwap is free to use (open-source), with community support and optional paid third-party consulting for enterprises needing integration.
FaceSwap is an open-source face-swapping toolkit that trains and applies autoencoder-based models to replace faces in images and video. The project emphasizes local GPU training and per-frame control, serving users who need reproducible deepfake pipelines rather than turnkey cloud services. Key capabilities include multi-detector face extraction (MTCNN/Dlib/RetinaFace), XSeg mask-based segmentation, and a Convert module for blending and color correction. FaceSwap sits in the AI Avatars & Video category for creators who need offline, auditable workflows. Pricing is accessible: core software is free, with only optional paid third-party support.
FaceSwap is an open-source face-swapping toolkit that trains and applies autoencoder-based models to replace faces in images and video. The project emphasizes local GPU training and per-frame control, serving users who need reproducible deepfake pipelines rather than turnkey cloud services. Key capabilities include multi-detector face extraction (MTCNN/Dlib/RetinaFace), XSeg mask-based segmentation, and a Convert module for blending and color correction.
FaceSwap sits in the AI Avatars & Video category for creators who need offline, auditable workflows. Pricing is accessible: core software is free, with only optional paid third-party support. FaceSwap's strongest citation-ready points are XSeg per-pixel face segmentation for mask accuracy and fewer blending artifacts, Supports MTCNN, Dlib and RetinaFace detectors for multi-detector face extraction, Autoencoder training using TensorFlow-based models with multi-GPU checkpointing.
Best-fit buyers should compare the product against direct alternatives using the same input data, expected output quality, collaboration needs, governance requirements and total monthly cost.
Three capabilities that set FaceSwap apart from its nearest competitors.
Which tier and workflow actually fits depends on how you work. Here's the specific recommendation by role.
FaceSwap is useful when one person needs faster output without adding a complex workflow.
FaceSwap should be tested for collaboration, quality control, permissions and repeatable results.
FaceSwap is worth buying only if the pilot shows measurable time savings or quality gains.
Current tiers and what you get at each price point. Verified against the vendor's pricing page.
| Plan | Price | What you get | Best for |
|---|---|---|---|
| Free | Free | Full desktop toolkit; local GPU required; community support only | Researchers and hobbyists with a local GPU |
| Community Support / Donations | Optional donations | Donations fund development; no paid SLA or commercial features | Casual users who want to support the project |
| Third‑party Consulting | Custom | Custom model builds, GPU training, integration (priced per project) | Enterprises needing bespoke integration and support |
Scenario: A small team uses FaceSwap on one repeated workflow for a month.
FaceSwap: Free | Freemium | Paid | Enterprise ·
Manual equivalent: Manual review and execution time varies by team ·
You save: Potential savings depend on adoption and review time
Caveat: ROI depends on adoption, usage limits, plan cost, output quality and whether the workflow repeats often.
The numbers that matter — context limits, quotas, and what the tool actually supports.
What you actually get — a representative prompt and response.
Choose FaceSwap over DeepFaceLab if you need open-source, community-driven local workflows and XSeg segmentation for production control.
Real pain points users report — and how to work around each.