GPT-Class On-Prem Serving for Pharma Trial Recruitment

Frequently Asked Questions

01.What does it cost to serve GPT-class models on-prem for trial recruitment?

A single-node pilot built on one 8-GPU H100 server typically runs 280,000 to 420,000 dollars in capital plus setup for the first year, market research range, based on component pricing for the GPU node, networking, and inference stack. A multi-node production deployment sized for a multi-site sponsor program typically runs 650,000 to 1.4 million dollars in year one, market research range, since no audited per-project figure is publicly available for this exact workload.

02.Why does HELM top-quartile latency matter for trial recruitment inference?

A coordinator screening a candidate during a live clinic visit has seconds, not minutes, to get a matching answer before the visit ends or the candidate leaves. Targeting the fastest quartile of HELM's denoised inference runtime distribution keeps the on-prem cluster's response time inside that screening window, which is the difference between coordinators using the tool and abandoning it after the pilot.

03.Can a sponsor start with a smaller on-prem pilot before the full cluster build?

Yes. A single 8-GPU node running a quantized open-weight model can validate latency, coordinator adoption, and data-residency posture on one or two protocols before a sponsor commits to the multi-node cluster and the networking fabric a full production deployment needs.