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Prism shipped a 27B that fits a laptop. We put it through a battery of agentic traps to see if it reasons like its size.
Read →A 27B model whose weights are all −1, 0 or +1 — what it takes to run, and how fast it goes.
Read →One layer of the filter between raw accessibility data and the agent — element routing, on the Neural Engine.
Read →How small can a model be and still learn a structured capability?
Read →Where ternary {−1, 0, +1} weights are the right tool for small, on-device models — and where they aren't.
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