Argmax Local Server

TL;DR

• Argmax's real-time transcription matches top cloud APIs on feature set and accuracy while providing consistently lower latency because we optimized it for the powerful Apple Neural Engine.
• However, Argmax SDK requires native integration which meant that migrating from the cloud required writing new code until now.
• Due to popular demand, we built Argmax Local Server so that migrating from cloud APIs does not require changing your implementation!
• It is now also easier to work with Argmax in non-native apps (Electron, Tauri), using clients in Javascript, Rust, Python and more.
• Argmax Local Server is feature-complete for AI Meeting Notes apps with multi-stream real-time transcription of system audio and microphone, custom vocabulary for names and more.

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Multi-stream Real-time Transcription

Run multiple independent audio input streams and get multiple real-time transcript output streams without additional memory consumption. Multi-stream is necessary when transcribing system audio, e.g. Google Meet audio from remote participants, and system microphone, e.g. Google Meet audio for local participants, in the same meeting.

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WebSocket API & Cloud API Compatibility

Argmax Local Server's WebSocket API is compatible with that of Deepgram. The demo video above demonstrates an Electron app using Argmax Local Server with ZERO changes to app code when migrating from Deepgram. This is possible by simply switching the inference host URL endpoint from remote host (api.deepgram.com) to local host (localhost).

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Other Apps Do Not Slow Down

‍Before Argmax Local Server hit the market, many apps like Granola tried on-device inference and decided against it because CPU and GPU resource contention with other apps led to slowdowns and user complaints.

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In our mission to make on-device the obvious architectural choice for audio model inference infrastructure, we solved this problem. See 1:31 in the video above for details on how.

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Real-time Speaker Diarization

Real-time speaker diarization will be added to Argmax Local Server (and SDK) in early 2026, get on the waitlist to be the first to hear when it ships! For now, we recommend using SpeakerKit via Argmax SDK for use with prerecorded audio.

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