Recursive SI releases Flint, a 40B open-weight coding model built with automated research

AIRecursive SI releases Flint, a 40B mixture-of-experts model with 2.5B active parameters and open weights under Apache 2.0. Its Eureka Machine contributed to nearly every part of the stack, from data and training recipes to inference kernels, and the team built the model in under four months.

elvis

@omarsar0

View on X

Bullish on automated AI research. Early signs of self-improving AI, no doubt.

Flint is the first model from @recursive_si. Their Eureka Machine contributed to nearly every part of the stack, from data and training recipes to the inference kernels, and the team built it from scratch in under four months!

It is a 40B MoE with 2.5B active parameters and open weights under Apache 2.0. It runs at 125+ tokens/s on an M4 Pro MacBook Pro at short contexts.

Highly recommend checking it out. We will be testing this in our internal autoresearch evals.

Richard Socher@RichardSocher

Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine. • Best-in-class fast local coding • Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark • Built from scratch in under 4 months Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.

View quoted post on X

Source details

elvis · x.comPublished Oct 21, 12:43 PM ET · added here 1:10 PM ET

Original title: Bullish on automated AI research. Early signs of self-improving AI, no doubt.

Recursive SI releases Flint, a 40B open-weight coding model built with automated research

Topics