Mistral Is SO Back: Inside Le Chonk, the West’s Biggest Open Model (Pierre Stock, VP Science, Mistral)

Mistral AI is back in the frontier AI race. Mistral Large 4, nicknamed “Le Chonk,” is a 1-trillion-parameter open-weight model, trained in two months on 3,800 GPUs in Mistral’s own European datacenters — and independently rated the best open model outside China alongside Meta’s Muse Spark Open. After a year when open-weight AI meant DeepSeek, Kimi, Qwen and GLM, October brought a wave of Western open models, with Mistral at the front of it. Pierre Stock, Mistral’s VP of Science and first employee, walks through how the model was built: mixture-of-experts explained, what Mistral borrowed from DeepSeek, reinforcement learning at scale on coding, cyber, finance and chip design, why the RL run is still going, the model that pinged its own trainer from inside the sandbox, open weights vs cyber refusals, why 10-trillion-parameter models are coming, and Mistral Large 5, already in pretraining. (00:00) Cold open (00:59) The Western open-weight comeback: Beam, Le Chonk, Muse, Nemotron (04:09) The US shutdown of Anthropic’s models — “AI is like electricity” (06:07) Why “Le Chonk” (07:56) “Mistral fell behind”: the comeback from the inside (10:29) Training on 3,800 GPUs in Mistral’s own datacenters (13:24) Meta keeps its best model closed, Mistral opens Chonk (15:40) Chonk vs Beam, Muse Spark Open and the Chinese models (18:44) Why Chinese labs are still at the frontier (21:08) Pierre’s story: FAIR, Yann LeCun, the “Mistral mafia” (25:14) From compressing networks to a trillion parameters (27:30) Mixture of experts explained: the hospital analogy (32:25) 10-trillion-parameter models are coming (35:29) What Mistral borrowed from DeepSeek (36:46) One model, several reasoning modes (39:15) Native multimodality: satellites, manuals, computer use (41:56) Data, synthetic data and model collapse (46:32) Reinforcement learning as an exam (49:59) Where the efficiency comes from (52:18) Le Chonk is still training right now (53:39) What RL trains on: coding, cyber, finance, chips (58:13) Partial rewards and looping penalties (59:58) Did RL teach anything new? pass@k (1:03:16) The sandbox story: the model that pinged its trainer (1:07:44) Open weights vs cyber refusals (1:12:05) Timestral: time series on a CPU (1:14:18) AI doing AI research (1:16:22) Coming up: Mistral Large 5