BitNet (bitnet.cpp)

bitnet.cpp is Microsoft's official inference framework for 1-bit LLMs, running BitNet b1.58 ternary models on ordinary CPUs with optimized I2_S and TL1 kernels built on the llama.cpp architecture. Because weights are constrained to -1, 0, and 1, the runtime achieves lossless inference with speedups of 2.37x to 6.17x on x86 CPUs and 1.37x to 5.07x on ARM, cutting energy use by roughly 55 to 82 percent versus full-precision baselines, and the team has demonstrated a 100B-parameter model running at 5 to 7 tokens per second on a single CPU. The repository ships the official BitNet-b1.58-2B-4T model (2.4B parameters) plus support for community conversions such as Llama3-8B-1.58 and the Falcon3 family, along with a conversational chat mode. Setup means cloning the repo, creating a conda environment, and building with CMake; no GPU is needed. Code is MIT licensed, the technical report is on arXiv (2502.11880), and at roughly 39.8k GitHub stars it is the reference implementation for the 1-bit LLM research direction.