llama.cpp b10295 fixes quantized tensor strides for accurate AI inference

llama.cpp, the wildly popular open-source project for running LLMs locally, just released maintenance snapshot b10295. The headline fix is in the model loader: it corrects quantized reshaped tensor strides (PR #26672). Quantized models compress weights into smaller data types to reduce VRAM/RAM usage, but reshaping them requires careful stride offsets. A bug there could cause the model to read memory incorrectly, leading to inaccurate outputs or a performance hit. This little patch eliminates that risk, ensuring quantized tensors are laid out exactly as the compute kernels expect.

The release also demonstrates llama.cpp's breadth: prebuilt artifacts are available for Apple Silicon (with and without KleidiAI), Intel x64, Linux on x86/ARM/s390x, Android, and Windows. GPU acceleration includes CUDA 12.4 and 13.3, Vulkan, ROCm 7.2, OpenVINO, SYCL, and OpenCL for Adreno. For developers who self-host AI models on mixed hardware, that means the fix is one download away—no manual compilation needed. With 123k stars and an active maintainer crew, llama.cpp remains a cornerstone of the local AI ecosystem, and releases like this quietly keep it solid.