llama.cpp b11170 Released with Qualcomm Hexagon Backend Fix
Open-source LLM inference engine llama.cpp released build b11170, introducing a bug fix to properly handle multi-sequence data in the `concat_2d` operation for Qualcomm Hexagon backends. This patch enhances hardware acceleration stability on Qualcomm Snapdragon platforms equipped with Hexagon DSPs and NPUs. It supports the broader trend of running complex AI models directly on edge devices such as ARM-based laptops and smartphones. The patch addresses pull request #29344, which corrects sequence concatenation behavior in Hexagon tensor operations. Pre-compiled binaries for Linux, Android, Windows ARM64 Snapdragon, macOS, and iOS were published as part of this automated release cycle.
## BACKGROUND
llama.cpp is a widely used C/C++ framework designed for low-latency local inference of Large Language Models on CPU, GPU, and specialized hardware accelerators. Qualcomm Hexagon is a Digital Signal Processor (DSP) and Neural Processing Unit (NPU) architecture built into Snapdragon processors to efficiently compute machine learning workloads.