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Renting Cloud GPUs vs. Buying Your Own: How to Choose for Deep Learning

A data-driven look at cost, flexibility, and performance—plus when Thunder Compute’s $0.57/hr A100s beat a desktop GPU.

Published:

May 19, 2025

Last updated:

May 19, 2025

TL;DR — If you’ll use a GPU fewer than ≈ 3,500 hours in its lifetime (≈ 3.4 years at 20 h/week), renting an NVIDIA A100 40 GB on Thunder Compute for $0.57/hr is cheaper than buying a desktop RTX 4090 now selling for ≈ $2,000. Skip the upfront cost, scale to 80 GB on demand, and start with $20/month in free credit → Get started.

1. Why this question matters

The question "rent vs buy GPUs for AI” keep climbing as models balloon and hardware prices stay volatile. The right answer depends on three variables:

Utilization (GPU-hours you actually need)
CapEx vs OpEx (cash today vs pay-as-you-go)
Practicalities (electricity, obsolescence, downtime)

We crunch real numbers below so you can plug in your own workload.

2. Current hardware prices (US, May 2025)

GPU	Street price*	VRAM	Launch year
NVIDIA A100 80 GB (SXM/PCIe)	$18–20 k	80 GB	2020
NVIDIA A100 40 GB	$8–10 k	40 GB	2020
NVIDIA RTX 4090	≈ $2.0 k	24 GB	2022

*Retail snapshots: A100 purchase prices (Modal), RTX 4090 price range. (ComputerCity)

3. Thunder Compute rental rates (on demand)

GPU	VRAM	Hourly	GPU-hours per $100
A100 40 GB	40 GB	$0.57	175 h
A100 80 GB	80 GB	$0.78	128 h

See full pricing.

4. Breakeven math

Breakeven hours = Purchase price ÷ Hourly rate

Scenario	Equation	Hours	Years @ 20 h/wk
Buy RTX 4090 vs rent A100 40 GB	$2,000 ÷ $0.57	≈ 3,509 h	≈ 3.4 yrs
Buy A100 40 GB vs rent same	$9,000 ÷ $0.57	≈ 15,789 h	≈ 15 yrs
Buy A100 80 GB vs rent same	$19,000 ÷ $0.78	≈ 24,359 h	≈ 23 yrs

(Electricity, cooling, and resale value not yet counted.)

5. Hidden costs of owning

Power & cooling. A RTX 4090 draws ~450 W. At $0.15/kWh that’s $0.067/h—adding $130/yr if you run 20 h/wk. (1)
Obsolescence. RTX 50-series launches this year; resale values drop fast. (2)
Downtime & maintenance. RMA, driver headaches, and capital locked in a single box.
Scale ceiling. Need 80 GB? You’ll still rent or upgrade.

6. Who should rent

User	Typical usage	Monthly cost on Thunder (A100 40 GB)	Why rent
Student / tinkerer	10 h/mo	$6	Zero CapEx; pay only when GPU in use
Indie dev / side-project	40 h/mo	$23	Cheaper than GPUs + electricity
Researcher w/ bursts	160 h in sprint months	$91	Spin up multiple A100s, then pause

7. Who might buy (or hybrid)

Full-time production > 40 h/wk, 24 GB fits. You may reach 4090 breakeven in ~3 yrs, though you’ll still miss 80 GB memory.
On-prem data-sovereignty needs. If data can’t leave your lab, hardware is mandatory.
HPC clusters with volume discounts. Enterprises often mix local GPUs for steady load and cloud for peaks.

8. Key takeaways

Renting stays cheaper until thousands of GPU-hours.
Cloud eliminates obsolescence risk and lets you right-size VRAM per project.
Thunder Compute’s A100s give you enterprise-class GPUs for < $1/hr, plus $20 free credit to prototype risk-free.

Ready to train? Spin up an A100 in 60 seconds → Try Thunder Compute now.

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