2.78 TFLOPS on a Fanless MacBook Air? Benchmarking Apple's M4 with MLX

(This article is an English translation of a post originally published in Japanese on my blog. You can read the original Japanese version here ) . My fanless M4 MacBook Air hit 2.78 TFLOPS in a matrix multiplication benchmark using Apple's MLX framework. Matrix multiplication (GEMM) isn't just a basic math problem; it's the beating heart of modern Machine Learning and Large Language Models (LLMs). By measuring how fast a machine can multiply huge matrices, we are essentially measuring its raw capability to run AI locally. Let's see what the M4 chip can do. < Test Environment > Machine: M4 Macbook Air Memory: 16GB Python: 3.10.11 Framework: MLX v0.28.0 1. Measuring Execution Time To measure the execution time, I used a simple matrix multiplication operation. 1.1 The Benchmark Script I've published the measurement script on GitHub Gist . Feel free to download it and test it on your own Apple Silicon Mac. Note: I ran the benchmark last summer. I have recently verified that the script stil