
The GPT-4 to SLM Migration Decision: When Smaller Models Are Good Enough and When They Will Cost You
Match models to tasks to cut AI costs-use SLMs for structured, high-volume work and reserve GPT‑4 for complex or multilingual cases.
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Field notes on shipping AI-native systems with human engineering judgement: architecture, modernisation, automation, and the tradeoffs in between.

Enterprises require SLMs for data sovereignty, compliance, security, and cost savings; vendors must offer self-hosted, VPC, or on‑prem options.