RunPod
by RunPod
PaidGPU cloud platform for AI inference and training, offering on-demand and serverless GPU computing at competitive prices for ML engineers and AI developers.
Overview
RunPod is a GPU cloud platform purpose-built for AI workloads — inference, training, and fine-tuning machine learning models. It offers both on-demand GPU pods (persistent virtual machines with full root access) and a serverless computing option that scales to zero, making it a flexible choice for AI developers who need GPU power without the complexity of traditional cloud providers.
The platform supports a wide range of NVIDIA GPUs from consumer-grade RTX cards to enterprise H100s, with a community cloud option for cost-conscious users and a secure cloud tier for production workloads. RunPod's serverless API lets developers deploy AI models as endpoints that auto-scale based on demand, paying only for active compute time.
RunPod is best suited for ML engineers, AI researchers, and startups running GPU-intensive workloads like training large language models, running Stable Diffusion, or deploying inference APIs. Its pay-as-you-go pricing and one-click templates make GPU computing accessible without long-term commitments.
Pricing
- Shared infrastructure with competitive rates
- RTX 3090 from $0.17/hr, A100 80GB from $1.64/hr, H100 from $3.49/hr
- Best for experimentation and non-critical workloads
- Dedicated infrastructure with higher reliability, data encryption, and uptime guarantees
- Suitable for production deployments
- Deploy models as auto-scaling endpoints
- Pricing approximately 2× on-demand rates but scales to zero when idle
- No charge during idle time
- Persistent storage for datasets and model checkpoints, shared across pods