We ran the same 16-category eval across qwen2.5-coder, deepseek-r1, gemma3, phi4-mini and the qwen3 family on three Apple Silicon configs. The results say less about the models and more about hardware sensitivity.
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Open the rate-limit table of any cloud AI provider and you find a meter on everything. Running local-first by default makes most of those limits disappear.
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Most AI tools treat data protection as something you configure. With a local-first architecture, the safe state is the default one, because the data never leaves the machine to begin with.
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If you can’t reproduce a routing decision, you can’t audit it. This is how the router stays deterministic without giving up score-based dispatch.
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Local-first architecture solves most of the Act’s compliance asks by default. We walk through which articles map to which engine guarantees.
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