Pixtral

Mistral: Voxtral TTS, Forge, Leanstral, & Mistral 4 — w/ Pavan Kumar Reddy & Guillaume Lample

Mar 30, 2026 · 54:02

Mistral releases Voxtral TTS, a 3B-parameter speech generation model using a novel autoregressive flow matching architecture and a 12.5 Hz neural audio codec developed in-house. Pavan Kumar Reddy and Guillaume Lample explain how the model achieves high quality and efficiency by predicting audio latents as a continuous distribution, enabling real-time voice agent applications. The episode details Mistral's stepwise multimodal strategy, starting with transcription and now speech generation, with full duplex voice agents as the next goal. Enterprise deployment via Mistral Forge allows fine-tuning on proprietary data, exemplified by training on rare languages or domain-specific jargon. Guillaume discusses merging capabilities (Mistral Small merging coding, reasoning, vision), commitment to open science through technical reports, and reasoning transfer from formal proofs in Lean. The episode also covers AI for science partnerships and hiring for research and forward-deployed engineering roles.

Best of 2024: Open Models [LS LIVE! at NeurIPS 2024]

Dec 23, 2024 · 37:29

Luca Soldani of AI2 and Sophia Yang of Mistral argue that open models in 2024 have exploded in number and performance, closing the gap with closed models, but face growing compute and data-access challenges. Soldani notes 2024 saw models like Qwen and Deepseek rivaling frontier closed-model performance, and fully open models like OLMo release full recipes including data, code, and intermediate checkpoints. He points out that pre-training requires 10K+ GPUs for state-of-the-art, while post-training can be done with as few as eight. Sophia highlights Mistral's release of over a dozen models in 2024, including Pixtral multimodal and Le Chat—a free chat interface with image understanding, canvas code execution, and web search. Soldani warns of data access diminishing due to content owners blocking crawlers and lobbying efforts labeling open source AI as dangerous, emphasizing the need to protect the open ecosystem.