Kyle Wiggers on BitNet


"According to the researchers’ testing, the model surpasses Meta’s Llama 3.2 1B, Google’s Gemma 3 1B, and Alibaba’s Qwen 2.5 1.5B on benchmarks including GSM8K (a collection of grade-school-level math problems) and PIQA (which tests physical commonsense reasoning skills).

"Perhaps more impressively, BitNet b1.58 2B4T is speedier than other models of its size —in some cases, twice the speed —while using a fraction of the memory.

"There is a catch, however. Achieving that performance requires using Microsoft’s custom framework, bitnet.cpp, which only works with certain hardware at the moment. Absent from the list of supported chips are GPUs, which dominate the AI infrastructure landscape.

"That’s all to say that bitnets may hold promise, particularly for resource-constrained devices. But compatibility is —and will likely remain —a big sticking point."

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