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Helicone vs Groq

HeliconeGroq

Bottom line: Helicone for teams wanting simple, cheap LLM logging; Groq for developers building latency-sensitive apps.

HeliconeHelicone

Open-source LLM observability and AI gateway in one line of code.

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GroqGroq

Very fast LLM inference on custom LPU hardware.

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Votes00
PricingFreemiumFreemium
CategoryCodingCoding
Tags
llm-observabilityai-gatewayopen-sourcemonitoringcaching
inferencellm-apilow-latencyopen-sourcehardware
Best for
  • Teams wanting simple, cheap LLM logging
  • Developers self-hosting an open-source gateway
  • Cost and usage monitoring across providers
  • Developers building latency-sensitive apps
  • Teams running AI agents
  • Voice and real-time product builders
Pros
  • Extremely easy integration via a one-line base-URL swap
  • Open source under Apache 2.0 and free to self-host
  • Tiny Docker image that runs almost anywhere
  • Gateway features like caching, failover, and rate limiting cut cost and improve reliability
  • Generous free tier of 10,000 requests per month
  • 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
  • Product is in maintenance mode after the Mintlify acquisition, with no roadmap
  • Long-term hosted-service viability is uncertain and migration may be needed
  • Usage-based overages mean the Pro price is a floor, not a cap
  • Short retention on lower tiers (7 days free, 30 days Pro)
  • Large price jump from Pro to Team for compliance features
  • 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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