Apple is exploring a partnership with PrismML, a Caltech spinout, to integrate extreme model-compression technology into future iPhone hardware. The startup utilizes ultra-low-bit weight architectures, such as 1-bit and ternary representations, to drastically reduce the memory footprint of large language models. This mathematical approach allows a 27-billion-parameter model like Alibaba’s Qwen 3.6 to shrink from 54 GB to under 4 GB, making it compatible with the 8 GB of RAM found in current Pro-tier iPhones.
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