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Koyeb vs Groq

KoyebGroq

Bottom line: Koyeb for aI startups deploying inference; Groq for developers building latency-sensitive apps.

KoyebKoyeb

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

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GroqGroq

Very fast LLM inference on custom LPU hardware.

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Votes00
PricingFreemiumFreemium
CategoryAi InfrastructureAi Infrastructure
Tags
serverlessgpuinferencescale-to-zerodeployment
inferencellm-apilow-latencyopen-sourcehardware
Best for
  • AI startups deploying inference
  • Developers wanting autoscaling
  • Cost-conscious GPU users
  • Developers building latency-sensitive apps
  • Teams running AI agents
  • Voice and real-time product builders
Pros
  • Scale-to-zero saves idle GPU cost
  • Per-second billing
  • Competitive H100 pricing
  • Broad GPU range up to B200
  • Global multi-region deployments
  • Exceptional inference speed on supported models
  • Competitive per-token pricing
  • OpenAI-compatible API is easy to adopt
  • Free tier with no credit card
  • Good fit for agents and real-time apps
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
  • Limited to a curated catalog of open models
  • No hosting of arbitrary custom weights
  • Model lineup changes over time
  • Corporate turbulence in 2026 (Nvidia deal, down round)
  • Free-tier rate limits are modest

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