Pierre Stock, vice president of science at Mistral, said that after three weeks of reinforcement learning and testing since first launching the 1-trillion-parameter ML4 model, also known as Le Chonk, the coding capabilities of the multimodal model have significantly improved after adding two extra reasoning modes: Low, medium, and high, that enable 52 billion parameters to be active at any given time. As a result, ML4 now tops open models such as GLM-5.3 from Z.ai on the Artificial Analysis Coding Agent Index while using 47% less tokens per task on average. On the Terminal-Bench 4.0 benchmark, which tests agentic coding in the terminal, ML4 climbed from 28% to 41%, tying GLM-5.3 as the best model for coding agents.
ai-devtools —
Mistral Lays Claim to AI Coding Crown
Mistral today made accessible the weights for the Mistral Large (ML4) model that have now been tuned to become what the company claims now provides the agentic coding capabilities of any model available.
Reported by devops.com.
