Local processing delivers faster responses, offline continuity, and reduces data-leak risk. For sensitive sectors (health, finance, government, legal, R&D, media), data sovereignty is critical and cloud-free AI is often the safest, most compliant choice—perfect for SMB teams standardising on business devices for hybrid working and home office.
Local AI avoids pay-per-token surprises and keeps IP internal. Think fixed capex (device) + management versus variable cloud API costs. For teams with daily AI interactions (support, sales, back office), on-device often wins at scale.
Do I really need an NPU?
Yes—for quiet, efficient AI tasks (notes, summarisation, noise suppression). For images/3D, the GPU still leads.
How many TOPS do I need?
Don’t chase a single number. Match your actual workload to whether it’s NPU- or GPU-bound.
Will my apps run on ARM (Snapdragon X)?
Many modern tools do but confirm critical apps for native support or the impact of emulation.
When do I need a GPU with 16–24 GB VRAM?
For 3D/visualisation, video enhancement, and larger generative models.
Confused by HP’s new G1i/G1a/G1q naming?
See our HP EliteBook guide that explains the new scheme (Intel=G1i, AMD=G1a, Qualcomm=G1q).
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J. Simon Leitner – Founder, COO – 840 articles published on Notebookcheck since 2005
I am one of the founders of Notebookcheck, which I dedicated myself with after my studies at the Vienna Technical University were completed. Computers have been an integral part of my daily activities since the time of the Commodore C64 and Atari 1040ST. Besides new technologies such as electric mobility and environmental technology, I am also interested in architecture and construction engineering.