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Portkey vs Groq

PortkeyGroq

Bottom line: Portkey for teams routing production traffic across many LLMs; Groq for developers building latency-sensitive apps.

PortkeyPortkey

Open-source AI gateway and control plane for production Gen AI.

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GroqGroq

Very fast LLM inference on custom LPU hardware.

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Votes00
PricingFreemiumFreemium
CategoryCodingCoding
Tags
ai-gatewayllmopsopen-sourceobservabilitygovernance
inferencellm-apilow-latencyopen-sourcehardware
Best for
  • Teams routing production traffic across many LLMs
  • Organizations needing governance and reliability tooling
  • Developers wanting an open-source, self-hostable gateway
  • Developers building latency-sensitive apps
  • Teams running AI agents
  • Voice and real-time product builders
Pros
  • Fully open-source, self-hostable gateway for data control and no lock-in
  • Access to more than 1,600 models through one API
  • Broad feature set spanning observability, guardrails, routing, prompts, and cost control
  • Transparent, relatively cheap entry with free and ~$49 tiers
  • Battle-tested at very large scale
  • 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
  • Adds a network hop and dependency in the critical request path
  • Log-volume-based pricing can get complex or expensive at scale
  • Free-tier logging caps and short retention are tight for real debugging
  • Self-hosting the open-source gateway shifts ops burden to you
  • It is a gateway and ops layer, not a full build-and-eval IDE
  • 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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