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Langtrace vs Helicone

LangtraceHelicone

Bottom line: Langtrace for lLM app developers; Helicone for teams wanting simple, cheap LLM logging.

LangtraceLangtrace

Open-source, OpenTelemetry-based observability for LLM applications

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HeliconeHelicone

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

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Votes00
PricingFreemiumFreemium
CategoryLlm ObservabilityLlm Observability
Tags
llm-observabilityopentelemetrytracingevaluationsopen-source
llm-observabilityai-gatewayopen-sourcemonitoringcaching
Best for
  • LLM app developers
  • RAG engineers
  • Platform teams
  • Teams wanting simple, cheap LLM logging
  • Developers self-hosting an open-source gateway
  • Cost and usage monitoring across providers
Pros
  • Fully open source and self-hostable
  • Built on the OpenTelemetry standard
  • Traces export to any observability stack
  • Supports Python and TypeScript
  • Covers models, frameworks, and vector DBs
  • 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
Cons
  • Smaller ecosystem than larger competitors
  • Fewer turnkey enterprise features
  • Evaluations can require manual effort
  • Requires OpenTelemetry familiarity for advanced setups
  • Managed cloud is less mature than incumbents
  • 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

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