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Comet vs Helicone

CometHelicone

Bottom line: Comet for mL/data science teams; Helicone for teams wanting simple, cheap LLM logging.

CometComet

MLOps platform for experiment tracking, model registry, and production monitoring

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HeliconeHelicone

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

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Votes00
PricingFreemiumFreemium
CategoryMlopsLlm Observability
Tags
experiment-trackingmlopsmodel-registrymonitoringreproducibility
llm-observabilityai-gatewayopen-sourcemonitoringcaching
Best for
  • ML/data science teams
  • Researchers tracking experiments
  • Teams needing a model registry
  • Teams wanting simple, cheap LLM logging
  • Developers self-hosting an open-source gateway
  • Cost and usage monitoring across providers
Pros
  • Mature, framework-agnostic experiment tracking
  • Useful free tier with generous storage
  • Straightforward per-seat Pro pricing
  • Model registry for versioning and staging
  • Production monitoring in enterprise tier
  • 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
  • Crowded experiment-tracking market
  • Advanced monitoring gated to enterprise
  • GenAI observability is a separate product (Opik)
  • Free tier has fair-usage limits
  • Deeper features require paid tiers
  • 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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