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...At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous compute infrastructure. The project’s focus on extreme quantization dramatically reduces memory footprint and energy consumption compared with traditional 16-bit or 32-bit LLMs, making it practical to deploy advanced language understanding and generation models on everyday machines. BitNet is built to scale across architectures, with configurable kernels and tiling strategies that adapt to different hardware, and it supports large models with impressive throughput even on modest resources.

Keystone is a lightweight multi-platform, multi-architecture assembler framework. Multi-architecture, with support for Arm, Arm64 (AArch64/Armv8), Ethereum Virtual Machine, Hexagon, Mips, PowerPC, Sparc, SystemZ, & X86 (include 16/32/64bit). Clean/simple/lightweight/intuitive architecture-neutral API. Implemented in C/C++ languages, with bindings for Java, Masm, Visual Basic, C#, PowerShell, Perl, Python, NodeJS, Ruby, Go, Rust, Haskell & OCaml available. Native support for Windows & *nix (with Mac OSX, Linux, *BSD & Solaris confirmed). Thread-safe by design. ...

...Instead, the RKH intention is to support just enough basic concepts of that powerful tools to facilitate the reactive-system modeling holding a solid, and efficient implementation. Broadly speaking, the RKH implementation has been designed from the ground up to be used in 8-bits platforms but can be easily adapted to 16 or 32-bits platforms.