Running the Kimi K3 Model on CPU Without GPU via

Portable engine for running the kimi-k3-in-c model on a single processor Project kimi-k3-in-c presents a portable solution for executing inference of the Kimi K3 neural network model. The model has an impressive size of 2.78 trillion parameters, yet the application is optimized to run on standard hardware without the need for graphics accelerators (GPU). To function, the system requires only 8.24 GB of RAM, making it accessible for local deployment even on machines with limited resources. The application is written in the C99 programming language and is completely independent of external libraries. It does not require installation of BLAS or specialized frameworks, ensuring maximum autonomy and ease of compilation. The only strict requirement for hardware is the presence of a fast NVMe SSD storage device. A minimum of 1.56 TB of free space is required to store the model checkpoint. The solution's performance is approximately 32.7 seconds per generated token when using 8 GB of RAM. Despite significant delays associated with the model's volume and CPU limitations, the project demonstrates the possibility of running giant language models in desktop conditions. The source code of the project is available at: https://github.com/FareedKhan-dev/kimi-k3-in-c