Compute Comparison
vs
All providers →

Cerebrium vs RunPod: GPU Compute Price Comparison

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Cerebrium and RunPod. Updated July 2026.

Provider Overview

Provider type
Specialist
Specialist
Founded
2022
2022
Headquarters
Cape Town, South Africa
San Francisco, CA
Billing model
Per-second usage
On-demand, Spot (interruptible)
Min commitment
None
None
Support tier
Standard
Community → Pro
Regions
2 regions
3 regions

Strengths & Best For

Cerebrium

Cerebrium is a serverless ML infrastructure platform that deploys H100, A100, and T4 GPU workloads in seconds using custom containers, enabling real-time LLM inference and fine-tuned model serving without managing any infrastructure. Per-second billing and fast cold starts make it highly cost-efficient for bursty AI inference APIs and model deployment pipelines. A top choice for ML teams that want to ship production inference endpoints quickly with minimal DevOps overhead.

Strengths
  • Serverless deployment
  • Fast cold starts
  • Custom containers
  • Simple pricing
Best For
Real-time inference APIsModel deploymentServerless AI
Visit Cerebrium
RunPod

RunPod is a community GPU cloud marketplace offering H100, A100, RTX 4090, and RTX 3090 instances on both on-demand and spot GPU rental plans, consistently among the lowest-cost options available. Its spot instances make it especially popular with indie AI developers running batch inference, image generation, and LLM fine-tuning on a budget. A serverless GPU option is also available for per-second billing on inference endpoints.

Strengths
  • Very competitive pricing
  • Wide GPU selection
  • Spot instances
  • Serverless GPU option
Best For
Budget-conscious developersExperimentationBatch inference jobs
Visit RunPod

Live GPU Pricing

Loading live prices…

Region Coverage

Popular Comparisons