EDITORIAL DRAFT — outline only. Not ready for publication. AI infrastructure decisions, part 6 of 6. Audience: people approaching a GPU hosting purchase.
Make the quote comparable before judging the price
[Open with two explicitly hypothetical quotes. Explain why the same GPU label or headline hourly rate may conceal different service boundaries and commercial commitments.]
Check what is included—and what is not
- [Hardware model, memory, dedicated/shared access, interconnect, CPU and storage.]
- [Network charges, minimum billing units, setup costs, support and managed services.]
- [Availability, reservation terms, service levels, remedies and delivery dates.]
- [Contract length, renewal, termination, data export and price changes.]
Ask for evidence against your workload
[Describe a small acceptance test with quality, latency and throughput criteria. Record hardware, model/version, precision, utilisation, workload, software and measurement date. Distinguish vendor benchmarks from independently reproduced results.]
Record the unknowns before committing
[Create a quote-review checklist and show how to normalise costs by region, currency, tax treatment, term and workload. Identify questions for procurement, security and legal review. Do not name a best supplier without evidence or imply guaranteed savings.]
Reader next step
[Invite a request for a shortlist discussion or introduction through /services/. First confirm the active project and whether supplier help is wanted. Share a brief only after agreement to a named supplier. Disclose any relevant payment before introduction; no guaranteed shortlist, meeting or supplier coverage. A reader or subscriber is not automatically a saleable lead.]
