14 local decision models tested on a 16 GB Mac: Wald most accurate, H2O fastest
WolframRvnwlf · x · 2026-10-14
The author benchmarked 14 local decision-model variants (15 configurations across two runtimes) on a 16 GB Apple M4 Mac mini for agent tasks.
- Two frozen German/English synthetic datasets: 96 cases for tool/action selection and evidence judgments, 192 cases for email routing, embedded instructions, completion and urgency; held-out tests of 72 and 144 cases
- Wald had the highest observed synthetic accuracy; H2O was nearly as accurate but faster
- On four real-email candidates, Wald became the preferred model for deciding whether a tracked step is complete
- Key takeaway: a small local classifier's confidence should never grant an agent permission to act
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