Helicone is a llm observability tool with a free tier. We looked at what you actually get, what real users say, and whether the price matches the value. Here's our take.
Helicone is worth it if you use it regularly. 5-minute proxy integration captures full traces, cost, and latency across 20+ providers provides good value for the right users.
💰 Bottom line: Free gets you open-source llm observability and ai gateway — logs every prompt, response, cost, and latency across 20+ providers with a one-line proxy or async sdk, plus caching, retries, and prompt experiments
For Free, here's what that buys you:
$0/mo ÷ 8 hours saved = $0.00 per hour of value
Compare that to hiring a $llm observability professional at $40/hour
Even at minimum wage ($15/hr), Helicone saves you $120 over doing it manually.
We're not here to sell you Helicone. Here's what you should know before buying:
Quick comparison (not a full review):
Langfuse is an open-source LLM observability and engineering platform providing tracing, prompt management, evaluations, and dataset management for production AI applications.
Langfuse: Better if you need Production AI teams needing comprehensive observability and evaluation
Helicone: Better if you need comprehensive features
LangSmith is LangChain's commercial observability, evaluation and prompt management platform for LLM apps and agents in production.
LangSmith: Better if you need Developer teams building production LangChain, LangGraph, RAG, or agentic LLM applications that need trace-level debugging and repeatable evaluations.
Helicone: Better if you need comprehensive features
AI observability platform for evals, production tracing, prompt management, and regression detection.
Braintrust: Better if you need Engineering teams building production LLM applications who need both monitoring and automated optimization. Ideal for companies with dedicated AI engineering resources who want to move beyond manual prompt tuning to data-driven optimization workflows.
Helicone: Better if you need comprehensive features
| Use Case | Verdict | Why |
|---|---|---|
| Freelancers | ⚠️ | Affordable for solo professionals |
| Students | ✅ | Free tier available for learning |
| Small Teams (2-10) | ✅ | Check if team features are available |
| Enterprise | ✅ | Enterprise features and support needed |
Helicone may have a learning curve for beginners. Consider starting with the free tier before committing to paid plans.
Helicone remains relevant in 2026 with Helicone has expanded session tracking and trace grouping in 2025, added experiment tracking with A/B testing for prompt variations with statistical significance analysis, broadened provider support to include AWS Bedrock, Groq, Together AI, and Fireworks AI, and introduced an AI Gateway product that unifies routing across providers with automatic fallback and key management. The platform also added prompt management with versioning and a template registry where teams can manage production prompts with full version history, an evaluation framework for systematic quality testing using LLM-as-judge scoring and custom evaluation functions, and the ability to create datasets from production logs for fine-tuning or evaluation workflows. Additional improvements include configurable alerting on cost thresholds, error rates, and latency spikes via webhooks, and deeper integrations with LLM frameworks including LangChain, LlamaIndex, CrewAI, and the Vercel AI SDK.. The llm observability market continues to grow, making it a solid investment for professionals.
The free tier covers basic needs but upgrading unlocks advanced features like premium functionality. Most professionals will need the paid version.
Compare the features you actually need against each plan to find the best value for your use case.
While there are other llm observability tools available, Helicone's feature set and reliability often justify its pricing. Compare alternatives carefully.
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Last verified March 2026