Compare · Facecast vs DeepFaceLive
DeepFaceLive is archived. Facecast is the maintained replacement.
DeepFaceLive — the open-source standard for live face swap — was archived on November 13 2024 by its original maintainer. The successor project, Deep-Live-Cam, is a Python/CLI codebase that still requires a Windows machine, RTX GPU, ~30GB of model files, and Python environment setup. Facecast replaces the entire pipeline with a browser tab and a $19.99/month commitment if you stay past the free trial.
Try Facecast free — no cardSide-by-side
| What matters | Facecast | DeepFaceLive |
|---|---|---|
| Maintained today | Yes — production since 2024 | No — archived Nov 13 2024 |
| Install / setup | Open a browser tab | Python env + 30GB+ .dfm model downloads + OBS routing |
| Hardware requirement | Any modern laptop including integrated GPU | Windows + DirectX 12 + RTX 2070+ recommended |
| Cost | 30-min free, then paid | Free (open source) |
| Cross-OS | macOS / Windows / Linux / Chromebook | Windows-only |
| Custom face training | Upload any portrait — no training | Train your own .dfm models (hours of GPU time) |
| Pre-trained model catalog | 5 PD presets bundled | Community .dfm model marketplace (varying quality) |
Where Facecast wins
- — No Python install, no model file downloads, no GPU driver tuning.
- — Runs on Mac and Linux (DeepFaceLive was Windows-only).
- — Custom face = upload a portrait. No training run, no .dfm file, no GPU hours.
- — Maintained — bug fixes ship continuously rather than left in archive.
Where DeepFaceLive wins
- — Free (open source). Facecast is a paid subscription after the 30-min trial.
- — Train your own face models for arbitrary identities — Facecast works off uploaded portraits without a separate training step but quality depends on the portrait.
- — Local processing = no cloud GPU dependency, no per-frame latency over the network.
- — Community .dfm model marketplace (quality varies, but breadth is real).
Verdict
If you have a Windows machine with a high-end RTX GPU, the patience to assemble a Python environment, and you want zero ongoing cost — Deep-Live-Cam (the DeepFaceLive successor) is still the right answer. For everyone else, particularly on Mac / Linux / Chromebook or without RTX hardware, Facecast is the maintained replacement that does most of what DeepFaceLive did without the install complexity. Different commitments to different users.
Frequently asked
Why was DeepFaceLive archived?
The original maintainer (iperov) marked the GitHub repository archived on November 13 2024 without a public explanation. The community successor is Deep-Live-Cam — a Python/CLI tool with similar architecture but a smaller userbase.
Can I import my DeepFaceLive .dfm models into Facecast?
No — Facecast uses a different model architecture (server-side InsightFace + custom enhancers) and does not accept .dfm files. Facecast's "custom face" feature works from uploaded portraits and adapts at swap time, no separate training step.
Is Facecast based on DeepFaceLive code?
No. Facecast's backend uses InsightFace (Apache 2.0) + GPEN enhancement (proprietary), running on our GPU servers. DeepFaceLive used a different lineage of face-swap models.