Recursive Introduces Flint Coding Model Built With AI

Recursive introduces Flint, an open weight coding model built largely through its Eureka Machine, according to Wired. Flint has 40 billion parameters and can run locally on computers with enough memory.

CEO Richard Socher said AI handled and improved most parts of the model pipeline. The Eureka Machine contributed to the base model training method, model architectures and code tuned for specific chips. Benchmarks supplied by Recursive indicate that Flint performs better on coding tasks than other models with similar sizes and architectures.

Wired tested Flint on a Mac with 48 GB of RAM. The model completed coding requests that included a command line task list, a program for finding research on recursive self improvement and a simple website.

Socher said the Eureka Machine remains under human oversight and can be stopped. He said the goal is for the Eureka Machine to reach full recursive self-improvement, still overseen by people who could stop it.

Recursive has raised $650 million at a $4.65 billion valuation from investors including Google Ventures, Greycroft, Nvidia and AMD Ventures, according to Wired.