llama.cpp b10214 adds n_embd_head, boosting multimodal model deployment

The llama.cpp project, a widely-used C++ library for efficient LLM inference, rolled out version b10214 on July 31. The update introduces `n_embd_head` support within the mtmd (multimodal transformer) component, a technical change that refines how embedding head dimensions are handled for certain model architectures. This is a subtle but important fix for developers running multimodal models locally, as it ensures correct tensor shape handling and improves compatibility across newer model formats.

Alongside the code change, the release offers a comprehensive set of pre-built assets for macOS (Apple Silicon and Intel), Linux (x64, arm64, s390x), Windows, Android, and OpenEuler—with backends ranging from plain CPU to Vulkan, CUDA 12/13, ROCm, OpenVINO, SYCL, and KleidiAI. This means developers can simply download the appropriate binary and run local inference immediately, rather than wrestling with compilation flags and dependencies. For AI engineers and tinkerers, b10214 is a low-drama but valuable update that keeps llama.cpp on pace with evolving multimodal model requirements.