.avif)
Powering the next generation of AI & high-performance computing.
Engineered for large-scale AI training, deep learning, and high-performance workloads, delivering unprecedented compute power and efficiency.
Why rent the RTX 3090 instead of buying?
Strong price-to-performance for AI and rendering
The RTX 3090's 24 GB GDDR6X VRAM makes it one of the highest-memory consumer GPUs available, capable of handling quantized LLM inference, diffusion model generation, and high-resolution rendering tasks that exhaust cards with less memory. For value-conscious workloads, it delivers competitive throughput without the cost of a data center GPU.
Pay only for what you use
Purchasing an RTX 3090 runs $800–$1,500 depending on availability and condition. Runpod's on-demand pricing lets you access the same hardware with no upfront capital, no idle hardware costs, no depreciation.
Deploy in seconds, scale or switch when you're ready
Provision an RTX 3090 instance in seconds. If your workload outgrows it, scale up to a higher-tier GPU without committing to new hardware. Runpod handles the infrastructure so you can stay focused on your project.
Use Cases
Popular use cases.
Designed for demanding workloads —learn if this GPU fits your needs.
Technical Specs
Ready for your most demanding workloads.
Essential technical specifications to help you choose the right GPU for your workload.
"The Runpod team has clearly prioritized the developer experience to create an elegant solution that enables individuals to rapidly develop custom AI apps or integrations while also paving the way for organizations to truly deliver on the promise of AI."
Amjad Masad
"Runpod is the only place I can deploy high-end GPU models instantly—no sales calls, no rate limits, no nonsense."
Daniel Chang
“The main value proposition for us was the flexibility Runpod offered. We were able to scale up effortlessly to meet the demand at launch.”
Josh Payne
“Runpod helped us scale the part of our platform that drives creation. That’s what fuels the rest—image generation, sharing, remixing. It starts with training.”
Matty Shimura
Comparison
Powerful GPUs. Globally available. Reliability you can trust.
30+ GPUs, 31 regions, instant scale. Fine-tune or go full Skynet—we’ve got you.
FAQs
Questions? Answers.
What are the current hourly rates for renting an RTX 3090 on Runpod?
For the most current pricing, see the Runpod pricing page.
How quickly can I access a rented RTX 3090?
Most RTX 3090 instances are available within minutes of initiating your pod. Select your GPU, choose a template or bring your own container, configure storage and ports, and deploy.
Can I rent multiple RTX 3090s together?
Yes. Runpod supports multi-GPU configurations, and the RTX 3090 supports NVLink, which enables efficient GPU-to-GPU communication when properly configured — effectively doubling memory capacity and throughput across two cards for large-scale training or parallel rendering.
When does renting make more sense than buying an RTX 3090?
Renting is the better choice for variable workloads, scaling experiments, or when you want to test a configuration before committing. Buying only makes sense with consistent, full-utilization workloads over a long horizon. For current rental rates to compare, see the Runpod pricing page.
What software environments are available for RTX 3090 rentals?
Runpod offers pre-configured templates for PyTorch, TensorFlow, CUDA/cuDNN, Jupyter, and popular diffusion frameworks including Stable Diffusion and ComfyUI. You can also bring your own Docker container for fully custom environments.
10,100,100,100
Requests since launch & 400k developers worldwide
