llama.cpp b10213 ships rotated KV cache quant support
New llama.cpp release b10213 cuts memory with rotated KV cache quantization across platforms.
Deep Dive
llama.cpp just dropped b10213, adding support for rotated KV cache quantization (#26180). The release ships pre-built binaries for macOS, Linux, Windows, Android, iOS, and openEuler, with support for CPU, CUDA, Vulkan, ROCm, OpenVINO, SYCL, and more. With 122k stars and 21.2k forks on GitHub, this project is clearly one to watch.
Key Points
- Adds rotated KV cache quantization (#26180) to shrink memory footprint during long-context inference.
- Ships pre-built binaries for macOS, Linux, Windows, Android, iOS, and openEuler with CUDA, Vulkan, ROCm, and OpenVINO backends.
- Project boasts 122k GitHub stars and 21.2k forks, cementing its role as the go-to local LLM runtime.
Why It Matters
Local LLM users get lower memory usage and faster inference with KV cache quantization support.