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Elgato Voice Focus vs Noise Gator

Elgato Voice Focus

elgato.com

Noise Gator

github.com

Side by side

FigureElgato Voice FocusNoise Gator
Price from—Free
Free plan—Yes
Free trial——
Open source——
WindowsYesYes
macOSYesYes
Plans published11
Spec score · AI Noise Cancellation Software7.7 (#8)7.6 (#9)

Plans

Elgato Voice Focus

  • Voice Focus standalone VST3/AU plugin$49.99, paid once

Elgato Voice Focus pricing →

Noise Gator

  • Noise GatorFree

Noise Gator pricing →

In their own words

Elgato Voice Focus

Elgato Voice Focus is an AI-powered audio effect for cleaning a user’s microphone during streaming, recording, meetings, video editing, music production, and podcasting. It targets background noise, room reverb, and echo while preserving vocal warmth and detail. Elgato says its models reconstruct missing vocal frequencies, and one slider ranges from light processing to full processing. The standalone plugin is VST3 for Windows and AU for macOS, working in software that hosts those effects, including streaming tools, video editors, and DAWs. Named integrations include OBS Studio, Adobe Premiere, DaVinci Resolve, Final Cut Pro, Logic, Pro Tools, FL Studio, and Audacity. Zoom, Teams, and Slack require routing through Wave Link. Voice Focus processes only the user’s microphone. Processing occurs on-device in real time, without cloud transmission, recording, or model training. The standalone lifetime license costs 49.99 USD as a one-time purchase, with three total activations; Wave Link includes it free for listed Wave devices.

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Noise Gator

Noise Gator processes microphone audio in real time to reduce noise, then sends the cleaned signal to a virtual audio device for other apps. It is free under the MIT license and runs on Windows and macOS. Discord, Teams, and Zoom are named as apps that can use the virtual device as a microphone input. DeepFilterNet is the default denoising engine, with dual-pass RNNoise as a lighter fallback. The audio pipeline also includes a highpass filter, suppression control, a voice-activity-driven noise gate, three-band EQ, and automatic gain normalization. Bluetooth headset audio is supported, and the device menu refreshes when devices connect or disconnect. The app can install VB-Cable on Windows or BlackHole on macOS automatically. Prebuilt binaries are available from GitHub Releases; the ZIP includes the executable and ONNX Runtime DLL. DeepFilterNet’s runtime and an approximately 8 MB model download on first use, with SHA256 verification. Settings are saved to a TOML file for the next launch, and headless mode supports scripted or server use. The latest listed release is v0.1.2. Building from source requires stable Rust 1.85 or later, plus MinGW-w64 or MSVC on Windows.

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