THtheturtletalks·Apr 7, 2026
Thank you, I have added localvoxtral[0] and fixed FluidVoice
0. https://github.com/T0mSIlver/localvoxtral
In Show HN: Ghost Pepper – Local hold-to-talk speech-to-text for macOST0mSIlver
localvoxtral
Swift2026–2026
T0mSIlver / localvoxtral
localvoxtral
Talk to your coding agents by voice. Realtime, fully local macOS dictation that streams words as you speak and grounds LLM polishing in the exact Claude Code session under your cursor — Ghostty, iTerm2, Terminal.app, even a herdr pane. 100% on-device on Apple Silicon.
2Distinct people
4Mentions
0Explicit recommenders
65GitHub stars
What to know before exploring
What it is
Talk to your coding agents by voice. Realtime, fully local macOS dictation that streams words as you speak and grounds LLM polishing in the exact Claude Code session under your cursor — Ghostty, iTerm2, Terminal.app, even a herdr pane. 100% on-device on Apple Silicon.
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Where it is used
No documented product use has been verified yet.
What people are saying
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by week4 dated mentions
Observed mentions: 2026-02-24 15:00:07 UTC to 2026-04-07 08:30:32 UTC. Weeks start Monday, UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Feb 23 | 2026-02-23 00:00:00 UTC | 2026-03-02 00:00:00 UTC | 3 | 1 | 2 |
| Mar 2 | 2026-03-02 00:00:00 UTC | 2026-03-09 00:00:00 UTC | 0 | 0 | 0 |
| Mar 9 | 2026-03-09 00:00:00 UTC | 2026-03-16 00:00:00 UTC | 0 | 0 | 0 |
| Mar 16 | 2026-03-16 00:00:00 UTC | 2026-03-23 00:00:00 UTC | 0 | 0 | 0 |
| Mar 23 | 2026-03-23 00:00:00 UTC | 2026-03-30 00:00:00 UTC | 0 | 0 | 0 |
| Mar 30 | 2026-03-30 00:00:00 UTC | 2026-04-06 00:00:00 UTC | 0 | 0 | 0 |
| Apr 6 | 2026-04-06 00:00:00 UTC | 2026-04-13 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
4 sourcesYour voxtral.c work was a big motivator for me. I built a macOS menu bar dictation app (https://github.com/T0mSIlver/localvoxtral) around Voxtral Realtime, currently using a voxmlx fork with an OpenAI Realtime WebSocket server I added on top.
The thing that sold me on Voxtral Realtime over Whisper-based models for dictation is the causal encoder. Text streaming in as you speak rather than appearing after you stop is a fundamentally different UX. On M1 Pro with a 4-bit quant through voxmlx it feels responsive enough for natural dictation, though I haven't done proper latency benchmarks yet.
Integrating voxtral.c as a backend is on my roadmap, compiling to a single native binary makes it much easier to bundle into a macOS app than a Python-based backend.
In Parakeet.cpp – Parakeet ASR inference in pure C++ with Metal GPU accelerationCongrats on the results. The streaming aspect is what I find most exciting here.
I built a macOS dictation app (https://github.com/T0mSIlver/localvoxtral) on top of Voxtral Realtime, and the UX difference between streaming and offline STT is night and day. Words appearing while you're still talking completely changes the feedback loop. You catch errors in real time, you can adjust what you're saying mid-sentence, and the whole thing feels more natural. Going back to "record then wait" feels broken after that.
Curious how Moonshine's streaming latency compares in practice. Do you have numbers on time-to-first-token for the streaming mode? And on the serving side, do any of the integration options expose an OpenAI Realtime-compatible WebSocket endpoint?
In Show HN: Moonshine Open-Weights STT models – higher accuracy than WhisperLargev3Show HN: Localvoxtral – Local real-time dictation on macOS with streaming STT
I built a native macOS menu bar app for real-time dictation that can run fully on-device.
Most dictation tools, even local ones, use Whisper or similar offline models: you record, then wait for the transcript. Localvoxtral uses Mistral's Voxtral Realtime, one of the first open-source speech models with a natively streaming architecture. Words appear as you speak, not after you stop. It feels closer to someone typing along as you talk.
Press a shortcut, speak, and text gets typed directly into whatever app you're in. No cloud, no subscription, no data leaving your machine.
Two backend options:
voxmlx on Apple Silicon: I forked voxmlx to add a WebSocket server and memory optimizations. Runs a 4-bit quantized model on an M1 Pro. Audio and inference stay fully on-device.
vLLM on NVIDIA GPU: tested on an RTX 3090, noticeably faster.
The app is
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native Swift (~97%), lives in the menu bar, and stays out of your way. Configurable shortcut, mic selection, auto-paste.
GitHub: https://github.com/T0mSIlver/localvoxtral
Pre-built DMG available in Releases