AI 导读
Recursive AI 发布其 Eureka Machine 自动化研究系统打造的首个模型 Flint，是一个 40B MoE、激活参数 2.5B 的本地编码模型，4 个月内从零构建，自动化系统参与了数据、训练配方到推理内核的各环节。
正文
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.
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.在 X 查看被引用的帖子
来源：elvis · x.com