#66th of 38 in VoiceFor voice, speech and music

whisperlivekit

Real-time streaming speech-to-text server with diarization and translation

Stars
11.2k
License
Apache-2.0
Last commit
Aug 2026
Last release
Aug 2026
Language
Python
Stars, last 29 weeks+1,283
31 Mar 2026: 9,875 stars7 Apr 2026: 9,916 stars14 Apr 2026: 9,963 stars21 Apr 2026: 10,046 stars28 Apr 2026: 10,076 stars5 May 2026: 10,141 stars12 May 2026: 10,186 stars19 May 2026: 10,218 stars26 May 2026: 10,257 stars2 Jun 2026: 10,310 stars9 Jun 2026: 10,350 stars16 Jun 2026: 10,370 stars23 Jun 2026: 10,397 stars30 Jun 2026: 10,422 stars7 Jul 2026: 10,446 stars14 Jul 2026: 10,465 stars21 Jul 2026: 10,490 stars28 Jul 2026: 10,511 stars4 Aug 2026: 10,528 stars11 Aug 2026: 10,556 stars18 Aug 2026: 10,575 stars25 Aug 2026: 10,912 stars1 Sept 2026: 10,949 stars8 Sept 2026: 10,979 stars15 Sept 2026: 11,010 stars22 Sept 2026: 11,053 stars29 Sept 2026: 11,077 stars6 Oct 2026: 11,100 stars13 Oct 2026: 11,130 stars20 Oct 2026: 11,158 stars

9,875 on 31 Mar 202611,158 on 20 Oct 2026

From GitHub's daily star counts.

Checked on GitHub.

Overview

WhisperLiveKit is a Python server that transcribes microphone or browser audio in real time using simultaneous-decoding policies (SimulStreaming, LocalAgreement) instead of re-running Whisper on fixed chunks. It exposes a native WebSocket at /asr, an OpenAI-compatible transcription endpoint and a Deepgram-compatible WebSocket, and ships a web UI and a Chrome extension. Backends include Whisper, MLX Whisper, Voxtral, Qwen3-ASR, Canary and FunASR SenseVoice.

Who it is for: Developers self-hosting live transcription, captions or meeting STT

Ranked among open-source alternatives to ElevenLabs (#6 of 10) and Otter.ai (#7 of 10).

Strengths

  • Serves OpenAI-style /v1/audio/transcriptions, Deepgram-style WebSocket and native /asr WebSocket
  • Many backends: Whisper, MLX Whisper, Voxtral, Qwen3-ASR, Canary, SenseVoiceSmall
  • Optional Sortformer speaker diarization and translation to and from 200 languages
  • One shared engine serves multiple concurrent sessions with per-session language

Weaknesses

  • Heavy extras (voxtral-hf, vLLM stacks) conflict and need separate environments
  • Qwen3 causal mode is English-only; vLLM causal and Metal paths are experimental
  • Qwen3 streaming plans one realtime session per GPU and needs an explicit language
  • Canary on CPU is slow; GPU strongly recommended for larger backends

What it needs

  • GPU optional
  • Docker + Compose
  • Needs PyTorch, NeMo (diarization, Canary), vLLM (optional Qwen3 backend)
  • Models: Whisper, MLX Whisper, Voxtral Mini, Qwen3-ASR, Canary-1b-v2
  • port 8000

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