Cheap Tricks
Three measured, zero-code or near-zero-code wins that belong in every Apple Silicon practitioner's kit, plus the reminder that they carry the platform's signature risk.
Raise the GPU wired-memory ceiling. By default macOS caps how much of
unified memory the GPU may wire;
sudo sysctl iogpu.wired_limit_mb=N raises it
(the classic thread↗).
A 192 GB machine goes from ~140 GB to ~184 GB of usable "VRAM", the difference
between a 70B model fitting or not. Undocumented, resets on reboot, occasionally
moved between sysctl names across macOS versions: the
async-copy story in miniature, run knowingly.
Read the bandwidth line on the spec sheet before profiling anything. Across
M-series tiers, decode tokens/sec tracks memory bandwidth almost linearly
(M5 Max megathread↗),
because decode is bandwidth. Practical
uses: hardware buying decisions (the Max's 4× bandwidth over the base chip buys
~4× decode; extra GPU cores beyond that buy
prefill, not chat latency), and sanity
checks (if your tok/s is far off bandwidth ÷ model bytes, something is broken:
go look).
Control thermals or your benchmark lies. MTPLX measured long-run throughput decay dropping from 50% to 6.7% just by locking fans to max. Laptop and fanless chips throttle under sustained ML load; a benchmark's first ten seconds and its steady state are different machines. Fan control (or a Mac Studio) is part of measurement methodology here, not an enthusiast quirk.
And one honorable mention that rounds out the platform picture: the ANE exists. The Neural Engine, the third matrix engine on the die after the GPU and AMX, reaches ~6.6 TFLOPS/watt (vs ~1 for the GPU) but speaks only Apple's model frameworks (Core ML, superseded for generative workloads by Core AI in the macOS 27 cycle, which adds a documented hook for custom Metal kernels); the community's reverse-engineering effort↗ to train on it through private APIs is equal parts impressive and cautionary. For Metal work its main relevance is knowing that some workloads (quantized-conv-shaped inference at low power) have a better home than the GPU, and that Apple's own frameworks may route there without telling you.
That's the glossary. SOURCES.md↗ has the full annotated list of repos, writeups, and people worth following to stay current.