Llama.cpp b8325 fixes Apple Silicon performance bug, adds new GPU backends

The open-source project Llama.cpp, maintained by the ggml-org team, has released a new commit tagged b8325. This update primarily addresses a technical bug in the Metal backend specifically for macOS and iOS devices. The fix corrects an issue with L2 norm scaling (referenced in GitHub pull request #20493), a mathematical operation crucial for maintaining numerical stability and accuracy in neural network computations, particularly on Apple's ARM-based Silicon chips. While seemingly minor, such low-level fixes are essential for ensuring models run correctly and efficiently on consumer hardware.

Alongside this core fix, the release includes updated pre-compiled binaries across a wide array of platforms, significantly simplifying deployment for users. Developers can now download ready-to-run versions for Windows (including CUDA 12.4 and 13.1 for NVIDIA GPUs, Vulkan, and experimental SYCL/HIP support), various Linux configurations (CPU, Vulkan, ROCm 7.2 for AMD GPUs), and specialized builds for Huawei's openEuler OS. This broad compatibility underscores Llama.cpp's role as a universal inference engine, allowing models like Meta's Llama 3 to run on everything from laptops to servers with diverse hardware accelerators.