Apple shows how much faster the M5 runs local LLMs compared to the M4
20 hours ago
- #Apple Silicon
- #Machine Learning
- #Performance Comparison
- Apple's M5 chip shows significant improvements over the M4 in running local LLMs, with performance boosts of 19-27%.
- MLX is an open-source framework by Apple for efficient machine learning on Apple silicon, supporting neural network training and inference.
- MLX LM allows developers to run Hugging Face models locally on Apple silicon Macs, including support for quantization to reduce memory usage.
- The M5's new GPU Neural Accelerators enhance matrix-multiplication operations, crucial for machine learning workloads.
- Apple compared the M4 and M5 in generating tokens for various models, highlighting the M5's superior memory bandwidth (153GB/s vs. M4's 120GB/s).
- Image generation on the M5 is more than 3.8x faster than on the M4.
- MLX leverages Apple silicon's unified memory architecture, allowing operations to run on CPU or GPU without moving memory.