Buyers underestimate on-prem AI hardware costs — expensive memory may be a cloud bull case
mobileraj · x · 2026-11-04
The author recounts a conversation with an enterprise leader whose company has deep on-prem deployment expertise. Asked why they don't leverage increasingly capable open-source LLMs as a differentiator, the leader said buyers consistently underestimate the hardware costs (especially memory) required for on-prem deployment.
From this, the author floats a counterintuitive thesis: expensive AI hardware may actually be a bull case for cloud providers, since they can finance capex and amortize it across a far larger customer base — an advantage individual enterprises can't replicate.
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