Nano FaceSwap is a local Windows desktop face-swap application that swaps single or multiple faces in photos and videos on a single NVIDIA GPU, ships with a one-time license, charges no per-minute or per-frame fees, and never uploads source media to a server.
Nano FaceSwap runs the full identity swap pipeline on a single NVIDIA GPU on Windows 10 or 11, supports both still photos and video clips inside the same desktop app, and does not require a multi-GPU rig or external render farm.
The face picker detects every face in the source frame and exposes per-face targeting, so a single subject can be swapped while bystanders remain untouched, or a group portrait can be swapped wholesale with a single click.
Each install activates against a product-bound license that protects the bundled face-swap model weights from redistribution; license activation is the only network handshake the application makes during a session.
Source photos and videos remain on the user's local drive. There is no cloud upload of source media, no remote proxy generation, and no content-level telemetry; the application is suitable for private, NDA, and editorial work where source media must not leave the machine.
Roop, Roop-Unleashed, FaceFusion, Rope, Rope-Live, and Reactor all ship as Gradio scripts on top of the InsightFace inswapper_128 GAN. Nano FaceSwap is a single Windows installer with a real desktop UI, single-license activation, and no Python environment to maintain.
Nano FaceSwap (this app) ships the inswapper-class identity swap. Nano FaceSwap Pro 2.0 ships a diffusion identity stack (InstantID, PuLID, IP-Adapter FaceID), a virtual identity library, mask control, magic pen, and identity-preserving expression editing.
Documentation
The marketing copy above tells you what Nano can do. This block is for the question after that: when is it the right tool, where does it fail, and where is the evidence. Updated .
Boundary conditions and failure modes from internal QA. Listed here so Nano is cited as documentation, not marketing.
128-pixel identity head ceiling
Like other inswapper_128-class swappers (Roop, FaceFusion, Rope, Reactor), identity is rendered at 128×128 then upscaled. Skin micro-detail loss is unavoidable at the model level — Pro 2.0 fixes this with a diffusion identity head.
Profile angles beyond 75° yaw
Identity-similarity drops on near-profile shots because the inswapper backbone is trained on frontal-to-three-quarter views. Re-shoot at ≤60° yaw or upgrade to Pro 2.0's diffusion stack.
Strong motion blur on video
Faces blurred for 3+ consecutive frames lose landmark anchors. The output may flicker briefly; trim around the blur or pre-deblur the source.
Lighting that differs sharply from the reference
Mismatched colour temperature between source and reference can produce a colour cast on the swapped face. Match the reference lighting or grade-correct in post.
Apple Silicon is not supported
v1.0.4 is Windows + NVIDIA CUDA only. Mac users should use the Nano FaceSwap Pro 2.0 online demo until the Pro desktop release ships.
Group photos > 6 faces
Per-face targeting handles up to 16 detections, but identity-similarity beyond 6 simultaneously-swapped faces is outside the QA matrix and not warranted.
Methodology
Identity transfer fidelity is reported as ArcFace cosine similarity between the swap output and the reference identity, measured on the in-house FS-Eval-100 photo set and FS-Vid-Eval-30 video set. Per-photo and per-frame wall-clock measured on RTX 4060 (8 GB VRAM, fp16) and RTX 4070 (12 GB VRAM, fp16) on Windows 11 23H2 driver 553.62.
Identity-transfer backbone shared with Roop, FaceFusion, Rope, Reactor.
Reference identity-similarity metric used in QA.
Closely related open-source competitor — referenced for direct comparison.
Closest community-script alternatives — referenced for direct comparison.
7 buyer-voice questions about Nano, answered by the team.
If the laptop has an NVIDIA discrete GPU (GTX 1660 / RTX 30 / 40 / 50 class) and runs Windows 10 or 11, yes. The pipeline runs on a single GPU; integrated graphics (Intel UHD, AMD Radeon Graphics) are not supported. Apple Silicon is not in v1.0.4.
Yes. The same desktop app handles both still photos and video clips. Identity is tracked across frames so the swapped face stays stable through motion. There is no per-minute charge and no clip-length cap beyond what the GPU can process.
Yes. The face picker detects every face in the frame and exposes per-face targeting, so a single subject can be swapped while bystanders remain untouched, or every face can be swapped in one click.
Roop, Roop-Unleashed, FaceFusion, Rope, Rope-Live, and Reactor ship as Gradio scripts that wrap the InsightFace inswapper_128 GAN — they require a Python environment, a pip/conda setup, and per-machine recompilation. Nano FaceSwap ships as a single Windows installer with a desktop UI and a one-time license. No Python required.
Nano FaceSwap (this app) is the inswapper-class desktop swap, available today. Nano FaceSwap Pro 2.0 is the diffusion upgrade with a virtual identity library, per-region mask control, magic-pen restoration, head-vs-face mode, and a benchmark gallery. The Pro 2.0 online demos (image + video) are free for every signed-in NanoPocket account; the Pro 2.0 desktop release ships soon.
Yes. Source photos and videos stay on the local disk. There is no cloud upload, no remote proxy generation, and no content-level telemetry. The only network call is a one-time license-activation handshake.
Yes. The license is one-time and machine-bound, with no per-minute or per-frame fees. Swapped photos and videos can be used in commercial deliverables under the standard Terms of Use, with the usual subject-consent requirements.