GoKawiilI flew from London to Google Cloud Next 2026 in Las Vegas. Ten hours with no in-flight wifi. I used the time to test how far a modern MacBook can carry engineering work on local LLMs alone.
Setup
A week old MacBook Pro M5 Max, 128GB unified memory, 40-core GPU.
Gemma 4 31B and Qwen 4.6 36B via LM Studio.
Top 100 most common docker images, top programming languages alongside with enough dependencies to build function sites with rich visualisations.
Countless CLIs - with opencode, rtk, instantgrep and duckdb being most used.
What I built
A billing analytics tool covering two years of loveholidays cloud spend. DuckDB underneath, with a custom UI for slicing the data along dimensions the standard dashboards don’t expose. It surfaced patterns and cross-service correlations that had been hard to uncover.
I was interested in exploring this area for a while, but I could never prioritise it against whirlwind of my other responsibilities. With 10 hours to spare, top of the range hardware and OSS model I decided to give it a go.
Alongside that, I processed roughly 4M tokens on smaller tasks: refactors, CLI scaffolding, documentation. For tight-scope work, Gemma and Qwen produced output comparable to the frontier models I normally use.
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