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DeepEval vs Helicone

DeepEvalHelicone

Bottom line: DeepEval for engineering teams treating evals like tests; Helicone for teams wanting simple, cheap LLM logging.

	DeepEval Open-source LLM evaluation framework with pytest-style testing. Visit	Helicone Open-source LLM observability and AI gateway in one line of code. Visit
Votes	0	0
Pricing	Freemium	Freemium
Category	Llm Observability	Llm Observability
Tags	llm-evaluationtestingopen-sourceragci-cd	llm-observabilityai-gatewayopen-sourcemonitoringcaching
Best for	Engineering teams treating evals like tests Teams gating deployments on LLM quality RAG and agent developers	Teams wanting simple, cheap LLM logging Developers self-hosting an open-source gateway Cost and usage monitoring across providers
Pros	pytest-style workflow fits developer habits 50+ research-backed metrics out of the box Apache-2.0 and free to use Covers RAG, agents, conversations, and safety Integrates into CI/CD for quality gates	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	Eval reliability depends on judge model/config Competitive, crowded evaluation category Richer collaboration features require Confident AI cloud LLM-as-a-judge adds model API costs Requires writing and maintaining test suites	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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