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Koyeb vs RunPod

KoyebRunPod

Bottom line: Koyeb for aI startups deploying inference; RunPod for mL engineers serving models.

KoyebKoyeb

Serverless cloud with scale-to-zero GPUs for AI inference and apps

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RunPodRunPod

GPU cloud for training and serverless AI inference with zero egress fees

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Votes00
PricingFreemiumPaid
CategoryAi InfrastructureAi Infrastructure
Tags
serverlessgpuinferencescale-to-zerodeployment
gpu-cloudserverless-gpuinferencemodel-trainingcompute
Best for
  • AI startups deploying inference
  • Developers wanting autoscaling
  • Cost-conscious GPU users
  • ML engineers serving models
  • Cost-conscious training workloads
  • Startups needing on-demand GPUs
Pros
  • Scale-to-zero saves idle GPU cost
  • Per-second billing
  • Competitive H100 pricing
  • Broad GPU range up to B200
  • Global multi-region deployments
  • Wide GPU selection from RTX 4090 to H100
  • Serverless endpoints scale to zero
  • Per-second billing for active execution
  • No data ingress or egress fees
  • Sub-200ms serverless cold starts
Cons
  • Flat plan fee on top of usage
  • Not a full hyperscaler feature set
  • GPU availability can vary
  • Less mature ecosystem than AWS/GCP
  • Enterprise controls still maturing
  • Pure pay-as-you-go with no free tier
  • Spot capacity can be interrupted
  • Availability of specific GPUs varies by region
  • Requires familiarity with Docker and ML tooling
  • No managed model catalog like some competitors

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