Tag: #apple-silicon
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 6 posts
6 posts are tagged #apple-silicon; the most recent was published on 2026-07-31.
Often tagged together: #local-llm 2 #macos 2 #mlx 2 #unified-memory 2 #ai 1
Most read in the last 90 days:
How a 26B Model Runs in 2GB of RAM — Resident Memory and Working Set Are Not the Same Number
TurboFieldfare, posted to Show HN on July 29, 2026, claims to run Gemma 4 26B-A4B on M-series Macs in about 2GB of RAM. 14.3GB is installed on disk, the only thing resident in RAM is a 1.35GB shared core, and the expert
2026-07-31 · 12 min read #ai#llm#quantization#apple-silicon#moeWhy the Mac mini Became an On-Device AI Machine — What Apple's Silicon Exec Said, and What He Left Out
Apple Silicon senior product manager Doug Brooks talked to The Deep View about demand for the Mac mini and Mac Studio and where on-device AI is heading. Why developers and small teams reach for this little desktop as a l
2026-07-11 · 6 min read #apple-silicon#on-device-ai#local-llm#mac-mini#inferenceA Deep Dive into apple/container — The Lightweight VM Approach to macOS Containers ♪ Listenable
We examine the limits of Docker Desktop and its single shared Linux VM on macOS, then analyze the one-VM-per-container model adopted by apple/container. The post covers the Container Machine feature unveiled at WWDC26, a
2026-06-12 · 19 min read #apple-container#virtualization#macos#docker#containerMLX Deep Dive — Apple's ML Framework for Apple Silicon: Unified Memory, Lazy Graphs, and the Mac-Native Flow (2026 Hands-On) ♪ Listenable
MLX is the array framework that Apple's ML team — the same people who previously built PyTorch and JAX — rewrote from scratch for Apple Silicon. The core thesis is one sentence: the M-series GPU shares RAM with the CPU,
2026-05-14 · 19 min read #mlx#apple-silicon#ml-framework#unified-memory#metalModern Computer Architecture — CPU Pipelines, Out-of-Order, Caches, Branch Prediction, Meltdown, Apple Silicon, ARM, RISC-V, SIMD, GPU Deep Dive (2025)
Why arrays beat linked lists, why a branch can be 10x slower, how M1 beat Intel. CPU pipelines, Out-of-Order, L1 to L3 caches, branch prediction, Meltdown/Spectre, Apple Silicon, ARM/x86/RISC-V, SIMD, GPU SM/Warp, HBM/CX
2026-04-15 · 15 min read #computer-architecture#cpu#cache#branch-prediction#apple-siliconRunning LLMs on Apple Silicon: Inside M4/M5 Architecture for AI Inference ♪ Listenable
A deep technical dive into Apple M4/M5 Unified Memory Architecture and its implications for LLM inference. Covers the Neural Engine, MLX framework, llama.cpp Metal backend, real benchmarks, and an honest comparison with
2026-03-18 · 14 min read #apple-silicon#m5#model-serving#unified-memory#mlx