BaseRT: Best-in-Class LLM Inference on Apple Silicon via Native Metal

arXiv:2607.00501v1 Announce Type: new Abstract: We present BaseRT, a native Metal inference runtime for large language models (LLMs) on Apple Silicon, and report the highest inference throughput on this hardware to date. Existing runtimes, including llama.cpp and MLX-based frameworks, incur overhead from abstractions not designed for Metal's execution model or Apple Silicon's unified memory topology. By building natively on Metal with chip-specific kernel fusion, unified memory-aware optimisation, and custom dispatch logic, BaseRT recovers performance that framework-based approaches leave on t

Source: arXiv cs.CL — read the full report at the original publisher.

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