Launch in minutes.
Get clusters up and running faster than traditional cloud providers.
Pay by the second.
Ultra-flexible, on-demand billing—no commitments.
Scale globally.
Spin up hundreds of GPUs with a single command.
"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
AI Apps
"RunPod is the only place I can deploy high-end GPU models instantly—no sales calls, no rate limits, no nonsense."
Daniel Chang
Research
“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
Inference
“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
Model Training
GPU Pricing
Thousands of GPUs across 30+ regions.
Simple pricing plans for teams of all sizes,
designed to scale with you.
GPU
Storage Pricing
Flexible, cost-effective storage for every workload.
No fees for ingress/egress. Persistent and temporary storage available.
Pod Pricing
Storage Type
Running Pods
Idle Pods
Volume
$0.10/GB/mo
$0.20/GB/mo
Container Disk
$0.10/GB/mo
$0.20/GB/mo
Persistent Network Storage
Storage Type
Under 1TB
Over 1TB
Network Volume
$0.07/GB/mo
$0.05/GB/mo
Container Disk
$0.10/GB/mo
$0.20/GB/mo
Gain additional savings with reservations.
Save more with long-term commitments. Speak with our team to reserve discounted active and flex workers.
FAQs
Questions? Answers.
Curious about unlocking GPU power in the cloud? Get clear answers to accelerate your projects with on-demand high-performance compute.
What sets RunPod’s serverless apart from other platforms?
RunPod’s serverless GPUs eliminate cold starts with always-on, pre-warmed instances, ensuring low-latency execution. Unlike traditional serverless solutions, RunPod offers full control over runtimes, persistent storage options, and direct access to powerful GPUs, making it ideal for AI/ML workloads.
What programming languages and runtimes are supported?
RunPod supports Python, Node.js, Go, Rust, and C++, along with popular AI/ML frameworks like PyTorch, TensorFlow, JAX, and ONNX. You can also bring your own custom runtime via Docker containers, giving you full flexibility over your environment.
How does RunPod reduce cold-start delays?
RunPod uses active worker pools and pre-warmed GPUs to minimize initialization time. Serverless instances remain ready to handle requests immediately, preventing the typical delays seen in traditional cloud function environments.
How are deployments and rollbacks managed?
RunPod allows deployments directly from GitHub, with one-click launches for pre-configured templates. For rollback management, you can revert to previous container versions instantly, ensuring a seamless and controlled deployment process.
How does RunPod handle event-driven workflows?
RunPod integrates with webhooks, APIs, and custom event triggers, enabling seamless execution of AI/ML workloads in response to external events. You can set up GPU-powered functions that automatically run on demand, scaling dynamically without persistent instance management.
What tools are available for monitoring and debugging?
RunPod offers a comprehensive monitoring dashboard with real-time logging and distributed tracing for your serverless functions. Additionally, you can integrate with popular APM tools for deeper performance insights and efficient debugging.
Clients
Trusted by today's leaders, built for tomorrow's pioneers.
Engineered for teams building the future.
