Show HN: iPhone ANE holds LLM tok/s while MLX and LiteRT thermal-throttle

Apple's release of a neutral, reproducible benchmark for local LLMs on Apple Silicon marks a significant development in the field of artificial intelligence, specifically for devices such as Mac, iPhone, and iPad, with models including MLX, llama.cpp, CoreML, and Apple Foundation Models. This means that website owners who rely on AI-powered tools and plugins, particularly those utilizing local LLMs on Apple devices, can expect more accurate and reliable performance measurements. The benchmark provides a standardized way to evaluate the performance of different LLM models, which can help website owners optimize their AI-driven content and applications for better user experience. For website owners, this development offers opportunities to fine-tune their AI bot tracking and llms.txt management. To take advantage of this, consider the following actionable tips: review your website's AI-powered plugins and tools to ensure they are optimized for Apple Silicon devices, utilize the benchmark to compare the performance of different LLM models, and update your llms.txt file to reflect the most efficient models for your specific use case, such as MLX or CoreML.