Voxtral TTS
6 statements across 1 episodes · 4 bullish · 0 bearish · 2 people on the record · first statement Mar 30, 2026 by Pavan Kumar Reddy · said 2 times in 1 episodes since 2026 · across every show →
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brought up most by Guillaume Lample (1)
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Mar 30, 2026 positive
Reddy: Mistral reduces flow-matching audio inference to 16 steps
“When you have a depth transformer, if you have K tokens, you need to do K autoregressive steps, right? Even though it's a small thing, it's like K steps, which is very latency heavy with flow matching. We were able to cut it down significantly, so we are able …”
Mar 30, 2026 neutral
Reddy: Voxtral TTS processes audio at 12.5 Hz, enabling 30-minute contexts
“So the model processes audio at 12.5 Hertz. So one second maps to like, Full point by tokens. So I think one minute is like seven pointy tokens. So you can get like up to 10 minutes in like eight K context window and get half an hour and 30 K context window.”
Mar 30, 2026
Reddy: Mistral chose autoregressive TTS to enable real-time streaming voice agents
“One of the main applications is voice agents and we want real time streaming and that's the use case. That's not the only use case, but that's one of the primary use cases we want to get to. So we pick the autoregressive approach for that.”
Mar 30, 2026 positive
Reddy: Voxtral TTS is a 3B model based on the Ministral architecture
“It's it came out with such good quality, and Guillaume was mentioning, yeah, it's a three B model it's based off of the ministral model that we actually released just a few months back, and insert trunk, and it mainly meant for like the TTS stuff, but they nee…”
Mar 30, 2026 bullish
Lample: Voxtral TTS matches leading models at a fraction of cost
“So we support nine languages and this is a pretty small model a three-dimensional model, so very fast, and also state-ups, yeah, very equal. Performed at the same level of the best model, but it's Much more efficient in terms of cost, and also much, in terms o…”