- Affordable RTX 5090 access is available via on-demand cloud GPU rental
- SaladCloud offers the lowest price at just twenty-five cents an hour
- Flexible GPU leasing provides users with powerful computing capabilities without upfront investment
Developers and researchers are increasingly turning to short-term GPU rentals to handle demanding AI workloads without the high cost of ownership, and renting a top-tier RTX 5090 graphics card costs far less than you might expect.
Several cloud platforms now offer Nvidia’s flagship $3000 GPU for short-term rental, with prices coming in at well under a dollar an hour.
The cheapest of the bunch we’ve seen so far is from SaladCloud, with prices starting at 25 cents an hour for a 32GB RTX 5090 instance.
Affordable choices
The company operates a decentralized cloud platform that offers access to over sixty thousand GPUs sourced from both consumer and data center systems.
SaladCloud allows full customization of GPU, CPU and memory allocations, allowing users to match performance levels to their workload requirements.
At $0.25 an hour, the platform undercuts most traditional providers. Renting an RTX 5090 for a full day on SaladCloud would cost around $6 in total, while a month of continuous use would cost around $180.
Users can choose between priority levels depending on job type and resource requirements.
Vast.ai, another GPU marketplace, lists RTX 5090 cards starting at around $0.32 per hour, depending on host reliability, bandwidth, and available CPU pairing.
An example listing shows a 32GB RTX 5090 paired with an AMD EPYC 9654 processor and 451GB of system memory running at approximately 109 TFLOPS.
Novita’s pricing is higher on average, with its RTX 5090 32GB on-demand rate at $0.63 per hour and $0.32 per hour for spot instances. Higher frequency configurations can reach $0.72 per hour, still very affordable.
While these options include predictable billing and centralized support, SaladCloud’s model presents a lower-cost alternative for users who are more focused on cost efficiency than managed services.
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