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Open-weight coding model runs locally on regular computers
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Here is an open-weight coding model you can run locally on your computer. It's a 40B parameter model with a mixture-of-experts architecture. It activates 2.5B parameters per generated token. 512K context window. This thing runs on regular computers! 125 tokens/sec on an M4 MacBook Pro. Good alternative to closed models, but make sure you check their usage guidance to understand the trade-offs.
RichardSocher@RichardSocher3d ago
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.