PeopleofSuperintelligence

Researcher

Jonas Amar

Also known as Jonas N. Amar

Jonas Amar is a machine learning researcher on Mistral AI's research team and a co-author of papers on reasoning, speech, coding, robotics and safety models. Before that work, he co-authored Stabl, a biomarker-discovery method from Stanford's Department of Anesthesiology, Perioperative & Pain Medicine published in Nature Biotechnology in 2024, and presented a cardiac MRI risk model at ESC Congress 2024. In June 2025, he co-authored Magistral, Mistral's first reasoning model, and went on to work on Voxtral, Devstral and the Ministral 3 family. His 2026 papers cover Voxtral Realtime speech recognition, Voxtral TTS voice cloning, the Robostral Navigate robot navigation model and the Shieldstral safety classifier.

Timeline

  1. 2024

    Stabl at Stanford

    With Brice Gaudillière and colleagues in Stanford's Department of Anesthesiology, Perioperative & Pain Medicine, he co-authors Stabl, a machine learning method that picks a sparse, reliable set of biomarkers from omic data. The paper appears in Nature Biotechnology in 2024.

  2. August 2024

    A cardiac MRI risk model

    At ESC Congress 2024 in August 2024, he presents a machine learning model that uses cardiovascular magnetic resonance to predict cardiovascular events in asymptomatic patients with known coronary artery disease. The talk is part of a session on clinical applications of artificial intelligence in cardiovascular imaging.

  3. June 2025

    Magistral, Mistral's reasoning model

    In June 2025, he co-authors Magistral, Mistral AI's first reasoning model, built on the company's own reinforcement learning pipeline. The team trains Magistral Medium on top of Mistral Medium 3 with reinforcement learning alone and open-sources Magistral Small under the Apache 2.0 license.

  4. July–August 2025

    Voxtral and Devstral

    In July 2025, he co-authors Voxtral, a pair of multimodal audio chat models, Voxtral Mini and Voxtral Small, that handle audio files up to 40 minutes long. In August 2025, he co-authors the report on Devstral-Small, a 24B open-source model for coding agents.

  5. 2025

    Digital twins for preterm birth

    In 2025, he co-authors the bioRxiv preprint "Single-cell-level digital twins for preterm birth prevention strategies" with Stanford's Gaudilliere lab. The lab's work pairs a drug-screening assay on a patient's own immune cells with a combination of aspirin and lansoprazole aimed at preventing preterm birth.

  6. January 2026

    The Ministral 3 models

    In January 2026, he co-authors Ministral 3, a family of dense language models in 3B, 8B and 14B sizes with image understanding. The models are derived through Cascade Distillation, an iterative pruning and distillation recipe.

  7. February–March 2026

    Voxtral Realtime and Voxtral TTS

    In February 2026, he co-authors Voxtral Realtime, a streaming speech recognition model that performs on par with Whisper at a 480 ms delay. In March 2026, he co-authors Voxtral TTS, a multilingual text-to-speech model that generates natural speech from as little as 3 seconds of reference audio.

  8. Since 2025

    Research at Mistral AI

    He works with Mistral AI's research team, which credits him on Magistral in 2025 and Voxtral TTS in 2026. In July 2026, he co-authors Robostral Navigate, an 8B vision-language model that guides wheeled, legged and aerial robots from monocular RGB images, and Shieldstral, a 3B-parameter multimodal safety classifier.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Mistral AI. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes Mistral AI. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.
  3. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Mistral AI. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  4. 5,000 frontier users would be 38.2% of the core labs' 13,100 reported staffIncludes Mistral AI. 5,000 frontier users would be 38.2% of the core labs' 13,100 reported staff. We test the estimate against 3,913 named model contributors and dated all-staff records across Google DeepMind, OpenAI and Anthropic, plus six additional frontier-grade labs.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Jonas Amar yet. Send us a free-licensed photo.

  1. Discovery of sparse, reliable omic biomarkers with Stabl - PMC pmc.ncbi.nlm.nih.gov. Checked 20 October 2026.
  2. ESC 365 - Machine learning model using cardiovascular magnetic resonance to predict cardiovascular events in asymptomatic patients with known CAD esc365.escardio.org. Checked 20 October 2026.
  3. [2506.10910] Magistral arxiv.org. Checked 20 October 2026.
  4. [2507.13264] Voxtral arxiv.org. Checked 20 October 2026.
  5. [2509.25193] Devstral: Fine-tuning Language Models for Coding Agent Applications arxiv.org. Checked 20 October 2026.
  6. Repurposed Drug Combination Therapy for Preterm Birth Prevention | Explore Technologies techfinder.stanford.edu. Checked 20 October 2026.
  7. [2601.08584] Ministral 3 arxiv.org. Checked 20 October 2026.
  8. [2602.11298] Voxtral Realtime arxiv.org. Checked 20 October 2026.
  9. [2603.25551] Voxtral TTS arxiv.org. Checked 20 October 2026.
  10. [2607.20785] Robostral Navigate arxiv.org. Checked 20 October 2026.
  11. [2607.25857] Shieldstral arxiv.org. Checked 20 October 2026.