
Silero VAD
One voice detector to rule them all
What it does
Stellar quality. Highly portable. No strings attached. Supports 8 kHz and 16 kHz. Models < one megabyte in size. Supports 30, 60 and 100 ms chunks. Trained on 100+ languages, generalizes well. One chunk ~ 1ms on a single thread. ONNX up to 2-3x faster.
Does a similar job
all alternatives →- IBI built a sub-500ms latency voice agent from scratchMar 2026 · ntik.me · ▲570
I built a voice agent from scratch that averages ~400ms end-to-end latency (phone stop → first syllable). That’s with full STT → LLM → TTS in the loop, clean barge-ins, and no precomputed responses. What moved the needle: Voice is a turn-taking problem, not a transcription problem. VAD alone fails; you need semantic end-of-turn detection. The system reduces to one loop: speaking vs listening. The two transitions - cancel instantly on barge-in, respond instantly on end-of-turn - define the experience. STT → LLM → TTS must stream. Sequential pipelines are dead on arrival for natural…

- BYBoost Your Voice AI Agents with Open-Source Ten VAD2025 · github.com · ▲8
Voice Activity Detection (VAD) is a crucial component for Voice AI, enabling more natural and efficient interactions. TEN VAD is an open-source solution designed to supercharge your Voice AI Agents with lightning-fast, human-like conversations! TEN VAD offers some key advantages: ONNX Support: Deploy on virtually any platform or hardware architecture! This means greater flexibility and easier integration into your existing systems. Superior Detection Accuracy: Experience noticeable improvements in voice detection, leading to fewer errors and more reliable performance. Smaller & Faster: Enjoy…
Microsoft AI (MAI) Voice-12025 · microsoft.ai · ▲120Highly expressive and natural speech generation model

Voxtral TTS by Mistral AIMar 2026 · mistral.ai · ▲156Multilingual TTS model with realistic and expressive speech
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