FIELD HUB · GPU, AI AND INFRASTRUCTURE

GPU Hosting & Local AI Infrastructure: Power, Costs and Multi-GPU

A practical path for choosing hardware, measuring electricity, understanding Vast.ai and calculating profitability without confusing gross revenue with profit.

Field dataAssumptions separatedNo return promised

Three studies grounded in observed data

01RTX 5090 on Vast.ai: observed gross revenue and power costNine observed daily totals, the arithmetic average and the costs still missing from a true net result.→02Two RTX 5090 at PCIe x8/x8: the complete host mattersPower, heat, RAM, NVMe, CPU lanes and network constraints from one operating host.→03Vast.ai verified vs unverified: what the logs can and cannot proveA timeline of verification, reliability and observed asking prices—without claiming causation.→

Recommended decision order

  1. Define the workloadGaming, local AI, rendering, compute rental and mixed use do not require the same VRAM or software.
  2. Validate the whole platformGPU, PCIe lanes, CPU, RAM, storage, PSU, case, ventilation and network must work together.
  3. Measure at the wallThe card TGP is not the complete system’s wall draw.
  4. Calculate netGross revenue minus power, fees, maintenance, management time, tax and hardware recovery.

Supporting guides and tools

Frequently asked questions

Do two 16 GB GPUs become 32 GB of VRAM?

Not automatically. Software must know how to split the model or tasks between cards. Capacity is not merged like ordinary system RAM.

Does verified status guarantee more rentals?

No. It can reduce some buyer uncertainty, but price, availability, reliability, VRAM, CPU, storage, network and demand also matter.

Is gross revenue enough to justify another card?

No. The decision should use measured net revenue and a downside case, not only the best days.

Share