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When creating a Compute instance, you can choose between GPU-powered and vCPU-only setups. Both work the same way in the console, but they’re built for different types of workloads. This guide helps you decide which one fits your needs.

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The short answer

  • Choose a GPU if you need parallel processing power for heavy workloads like AI, rendering, or simulations.
  • Choose a vCPU if you’re running general-purpose applications, background tasks, or smaller workloads that don’t benefit from GPU acceleration.

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Key differences

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When to use GPU instances

Pick a GPU instance if your workload depends on massive parallelism or requires specialized acceleration. Examples:
  • Training or fine-tuning AI/ML models
  • Running inference with frameworks like vLLM
  • Video rendering and encoding
  • Scientific modeling or simulations
  • Any workload that runs faster with GPU acceleration

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When to use vCPU instances

Pick a vCPU instance if your workload doesn’t benefit from GPU acceleration. Examples:
  • Hosting lightweight web servers or APIs
  • Running development and test databases
  • Automating builds and deployments (CI/CD pipelines)
  • Running scripts and background jobs
  • Always-on services that need to stay cost-efficient

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How to decide

Ask yourself two questions:
  1. Does my workload rely on parallel processing?
    If yes → GPU is usually better.
  2. Do I need the lowest cost for general-purpose compute?
    If yes → vCPU is the simpler and cheaper option.
You don’t need to commit forever. You can start with vCPUs for development and testing, then move to GPUs when you’re ready to train or deploy heavier workloads.