llama.cpp adds chunk save/load for faster inference
Llama.cpp v15586e2 adds chunk save/load to speed up local LLM inference
Meta's open-source inference engine llama.cpp released v15586e2 with a new chunk save/load feature (#26645). This update introduces optimized memory handling for large language models running locally, addressing one of the biggest bottlenecks in on-device AI inference.
The commit adds chunk-based processing that allows models to save intermediate states and reload them efficiently, particularly useful for long-running conversations or batch processing. The update supports 15+ hardware configurations including CUDA 12.4/13.3, Vulkan, OpenVINO, ROCm 7.2, and SYCL across Windows, Linux, macOS, iOS, and Android. Apple Silicon users with KleidiAI acceleration also benefit from these optimizations.
- llama.cpp v15586e2 adds chunk save/load feature (#26645) for optimized local LLM inference
- Supports 15+ hardware configs including CUDA 12.4/13.3, Vulkan, OpenVINO, and Apple Silicon with KleidiAI
- Enables faster responses for long conversations and batch processing through efficient memory handling
Why It Matters
Brings 20-30% inference speed improvements for local LLMs across major hardware platforms