# GPU servers for universities and research labs, on fixed budgets

> GPU servers for universities and research labs: fixed monthly prices for grants and semesters, invoices for procurement and term pricing. Plan a semester.

Source: https://overgpu.com/solutions/universities  
Updated: 2026-10-23  
Publisher: OverGPU (https://overgpu.com/)

## Key points

- **Teaching servers:** Give a course its own GPUs for the semester, then cancel before the next renewal.
- **Shared lab machines:** One 8-GPU server for a research group, with your own accounts and scheduler.
- **Fixed monthly budget:** A flat price billed in advance, known before the month starts, with no egress fees within the included bandwidth.
- **Invoices for procurement:** An invoice for every server payment and renewal, and a receipt for every top-up, in your dashboard.
- **Term pricing by ticket:** With an active server, ask for 6–12 month or multi-server pricing to match a grant period.
- **Your data stays yours:** We access it only to operate or repair the service at your request or when required by law, and disks are securely erased between customers.

## Recommended configurations

- [NVIDIA H100 SXM](https://overgpu.com/gpus/nvidia-h100): $2,190 per month — One H100 per course or research project, billed monthly
- [8× NVIDIA HGX H100](https://overgpu.com/gpus/nvidia-h100): $16,900 per month — 8× H100 as a shared lab server for a research group
- [NVIDIA RTX PRO 6000 Blackwell](https://overgpu.com/gpus/nvidia-rtx-pro-6000): $1,390 per month — 96 GB for teaching labs where several students share a GPU

## Overview

GPU servers for universities and research labs work best when the cost is as predictable as the academic calendar. We rent dedicated NVIDIA and AMD GPUs by the month, at a flat price billed in advance, so a lab can match GPU spend to a grant line or a semester and stop paying when the work ends. Each server is assigned to your institution only, with root access, so you decide how students and researchers share it.

## Budgeting GPU servers for universities and research labs

Monthly billing maps cleanly onto academic budgets. A 15-week semester spans four billing months, so one H100 for a course costs 4 × $2,190 = $8,760. A research group sharing an HGX H100 node for six months pays 6 × $16,900 = $101,400 before any term pricing, which you can ask for by ticket once your server is active, for periods of 6–12 months or for several servers. For the mechanics, see [how billing works](https://overgpu.com/help/how-billing-works).

- The price is fixed for each paid month, and any change for future months comes with at least 30 days' notice.
- There is no setup fee and no egress fee within the included bandwidth: 20 TB a month on single-GPU plans and 50 TB on 8-GPU servers.
- Prices are in USD and exclude VAT and other taxes, which are added where applicable.
- Plans renew automatically from your account balance, with an email reminder before each renewal. Cancel from your dashboard before the renewal that follows the end of term and you stop paying; see [renewals and cancellation](https://overgpu.com/help/renewals-and-cancellation).

## GPU servers for teaching

For a course, size the GPU to the largest exercise, then decide how students share it:

- **Intro deep learning** with CNNs and small transformers runs well on an RTX 5090 with 32 GB or an L40S with 48 GB.
- **LLM courses:** a QLoRA exercise on a 7B–8B model needs roughly 10–20 GB including activations, so several students can share one 96 GB RTX PRO 6000 if jobs are scheduled. A 70B QLoRA project needs about 40 GB for the base model, which suits one H100 per team.
- **Sharing:** create Linux accounts, give each student a container, and assign GPUs with `CUDA_VISIBLE_DEVICES` or a scheduler. Jupyter and VS Code both work over SSH, as described in our [remote development guide](https://overgpu.com/docs/remote-development).

Whole GPUs are never sliced or shared with other customers, so the only contention is the one you manage among your own students.

## Shared lab servers for research groups

An HGX H100 node gives a group eight 80 GB GPUs on NVLink, 2 TB of DDR5 and eight 3.84 TB NVMe drives. Installing Slurm on the node lets jobs queue fairly and request one to eight GPUs each. Groups training larger models can step up to an HGX H200 node with 1.13 TB of HBM3e. For simulations and FP64 workloads, our page on [GPU servers for research and HPC](https://overgpu.com/solutions/research-hpc) compares the H100, H200 and MI355X.

You keep all rights to your data, and we access it only to operate or repair the service at your request, or when required by law. Local storage is not backed up unless agreed in writing, so keep copies on institutional storage, and check with your data office before uploading regulated or human-subject data. When a server is returned, its disks are securely erased.

## An example course plan

Suppose a 40-student course runs weekly QLoRA labs on 8B models, then ends with team projects on a 70B model. At roughly 10–20 GB per job, one 96 GB RTX PRO 6000 holds about four to nine jobs at once, each running slower while they share the card, so two of them carry a lab section working in pairs with a simple queue. For the final month, ten teams of four each get one H100, where the 4-bit 70B base takes about 40 GB.

- Two RTX PRO 6000 servers for the four-month term: 2 × 4 × $1,390 = $11,120.
- Ten H100 servers for the final month only: 10 × $2,190 = $21,900, with volume pricing worth asking for by ticket at that quantity.

Cancel each server before its next renewal and the spend stops with the course. Because the price per month is known in advance, this plan can go into a budget request before the semester starts.

## Procurement, invoices and payment

Ordering follows four steps in one form on the [deployment page](https://overgpu.com/deploy): you choose a configuration; set up the OS image, optional preinstalled software and your login (root password or SSH key); create a free account or log in; and pay the first month from your prepaid balance. The configuration and price are shown before anything is paid, which helps when a purchase needs internal approval, and once you pay, the server is delivered in under 10 minutes, with the IP and SSH details in your dashboard. The balance is in US dollars and is topped up in crypto: Bitcoin (BTC), Ethereum (ETH), Monero (XMR), Tether USDT on TRON (TRC-20) or Solana (SOL), from $100 to $10,000 per top-up, with +5% bonus credit for every full $100 in one top-up, up to +50% from $1,000; bonus credit is spent after paid credit, has no cash value and is not refundable. Card payments are not available yet, so check with your finance office that it can pay in crypto. Every server payment and renewal comes with an invoice, and every top-up with a receipt, in your dashboard; see [invoices and VAT](https://overgpu.com/help/invoices-and-vat). For large orders we may ask for verification, such as institution details and the identity of the person ordering, and export control and sanctions rules apply to every order.

## When a monthly server is the right fit

If your university's HPC center offers allocations and its queue fits your deadlines, use it. A monthly server makes sense when queue waits block a paper or a thesis, when you need root access or a GPU your cluster lacks, or when a course needs dedicated GPUs on fixed dates. For jobs that run only a few hours a month, hourly rental elsewhere will cost less.

To get started, [deploy your servers](https://overgpu.com/deploy) before term: they are delivered in under 10 minutes after payment, and the first month starts on the day of delivery. Answers to questions about course or project needs are in our help center, docs and calculators.

## Frequently asked questions

### Can we get pricing for a whole grant period?

Yes, once you have an active server: ask by ticket from your dashboard. Volume and term pricing covers 6 to 12 months or several servers, usually from three.

### Can several students share one GPU server?

Yes. The server is dedicated to your institution, and you create the accounts, containers or scheduler that share it among students; GPUs are never sliced or shared with other customers.

### How do we stop paying at the end of the semester?

Cancel from your dashboard before the next renewal date, with no fee. The server runs until the end of the paid month, then it is decommissioned and its disks are securely erased, so copy your data off first.

### Which payment methods can a university use?

Crypto: Bitcoin (BTC), Ethereum (ETH), Monero (XMR), USDT on TRON (TRC-20) or Solana (SOL), used to top up a prepaid balance in US dollars. Card payments are coming soon, and every server payment comes with an invoice in your dashboard.

### How far ahead should we order for a course?

Single-GPU and 8-GPU servers are delivered in under 10 minutes after payment, including when stock is limited, and the first month starts on the day of delivery.

## Related pages

- [GPU servers for research and HPC, on fixed monthly budgets](https://overgpu.com/solutions/research-hpc): H100, H200 and MI355X with vendor FP64 figures, CUDA or ROCm, on fixed monthly budgets. Match the GPU to your code.
- [How GPU server billing works](https://overgpu.com/help/how-billing-works): A flat monthly USD price, paid in advance from a prepaid balance you top up in crypto. No setup or egress fees.
- [Your GPU server invoice and VAT](https://overgpu.com/help/invoices-and-vat): An invoice for every server payment, a receipt for every top-up, and your VAT number on invoices. Here is how.
- [How to cancel GPU server rentals](https://overgpu.com/help/renewals-and-cancellation): Cancel GPU server rental any month with no fee, from your dashboard before the renewal date. Your server runs to the end of the paid month. See the steps.
- [Rent NVIDIA H100 SXM servers from $2,190 per month](https://overgpu.com/gpus/nvidia-h100): Rent a dedicated NVIDIA H100 SXM for $2,190/month (about $3.00 per GPU-hour at 24/7) or an 8-GPU HGX H100 for $16,900. Flat price, delivered in under 10 minutes.
- [RTX PRO 6000 vs H100: more memory or more bandwidth?](https://overgpu.com/compare/rtx-pro-6000-vs-h100): 96 GB of GDDR7 for $1,390 a month or 80 GB of HBM3 with NVLink for $2,190. See which suits 70B inference or multi-GPU training.