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Screenshot of mistral.ai: Voxtral 3

First screen, captured 5 days ago.

Voxtral 3

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Mistral AI announcement page for Voxtral 3, its speech and audio AI model.

What HN thinks

Mistral ships a slick new voice model, and the crowd mostly asks where the download button went.

Closed weights are a letdown
Many are disappointed that Voxtral 3 isn't open weight like its predecessor, which makes it useless for local or private deployments.
Local alternatives already excel
Commenters point to Parakeet, Kokoro, Qwen and other open models as fast, accurate local STT/TTS options that reduce interest in a paid cloud API.
Quality and language gripes
Some find the new voices more artificial than Voxtral 1, criticise missing European languages, and joke about accents and an unrealistically fast French dermatologist booking.

Consensus: Most agree the closed release is a step back from Mistral's open Voxtral models and that strong open local speech models like Parakeet are already good enough for many uses.

Recommended in the comments

Parakeet (library): Fast even on CPU, with low WER and roughly 10x the speed of Whisper.
Kokoro ↗ (library): Praised as the best-sounding local TTS, and small enough to run in real time on phones.
Pocket TTS ↗ (library): Recommended as a great local TTS, though it supports only a few languages.
FUTO ASR4All ↗ (library): They stream in real time on a single CPU thread and can run client-side through WASM.
SubSync ↗ (tool): It finds many sync points, so it fixes drift and offsets line by line.
Bazarr ↗ (tool): Suggested as the common choice for subtitle syncing in *arr setups.

Summarised by Claude from the comment thread 3 days ago.

Points: 747
Comments: 200
Posted: 2026-10-20 by ilreb
Category: Ai ml

mistral voxtral speech-recognition audio-models llm

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