What GPUs does RunPod offer?

RunPod offers A100, H100, RTX 4090, and other AI-grade GPUs available on both on-demand and spot pricing, billed per second.

Can I run LLMs on RunPod without managing servers?

Yes, RunPod supports serverless GPU endpoints that autoscale to zero when idle, and provides pod templates for vLLM and other LLM inference frameworks.

RunPod

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GPU cloud platform for AI inference and training — on-demand and spot instances billed per second.

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What is RunPod?

RunPod is a GPU cloud platform built for AI inference and training workloads. It provides on-demand and spot GPU instances for running models, fine-tuning, and serverless AI endpoints — with per-second billing and data centers across North America and Europe.

What can RunPod do?

On-Demand and Spot GPU Instances
Rent GPU instances by the second with on-demand (guaranteed) and spot pricing across A100, H100, RTX 4090, and other AI-grade GPUs.
Serverless GPU Endpoints
Deploy AI model inference as serverless endpoints that autoscale to zero when idle, with per-request pricing to avoid idle charges.
Pod Templates
Launch pre-configured pod environments for PyTorch, ComfyUI, Stable Diffusion, Axolotl, and other AI frameworks without manual setup.
Network Volumes
Attach persistent network storage across pods so model weights and datasets persist between GPU sessions without re-downloading.
vLLM and LLM Inference Support
Deploy LLMs with optimized vLLM inference backends for production-scale language model serving with batching and streaming.

Who is RunPod for?

ML engineers: Fine-tune open-source LLMs like LLaMA on large datasets using spot GPU instances to minimize compute costs during experimentation.
AI developers: Deploy a custom Stable Diffusion checkpoint as a serverless endpoint that autoscales based on request volume without paying for idle capacity.