Helicone vs Langfuse
Features, pricing and Editor Score side by side — to help you pick the right coding & development tool in 2026.
Quick verdict
On our Editor Score, Helicone and Langfuse land almost level. Pick Helicone if you want request logging across every major LLM provider; choose Langfuse for hierarchical tracing across model calls, tool invocations and retrieval steps. On pricing, both ship a free or freemium tier, so you can try each before paying.
Helicone vs Langfuse at a Glance
| Pricing | Freemium | Freemium |
| Free tier | ||
| Best for | request logging across every major LLM provider | hierarchical tracing across model calls, tool invocations and retrieval steps |
Helicone
Helicone is open-source LLM observability and an AI gateway. It logs and analyses requests across OpenAI, Anthropic, Gemini, Mistral, Groq, Together and OpenRouter, with sessions, user-level tracking, a query language, prompt management, datasets, a playground, rate limits and alerts.
- Covers the failure everyone hits — being unable to reconstruct what an AI feature actually did
- Session view makes multi-call interactions debuggable rather than guessable
- Per-user cost attribution reveals a spend distribution that totals completely hide
- Gateway positioning is what makes caching, routing and rate limiting possible at all
- Gateway mode puts a new dependency in your request path, with latency and availability consequences
- No latency overhead figures are published for that gateway position
- The open-source licence is not stated on the pages we read
Langfuse
Langfuse is an open-source LLM engineering platform covering tracing, evaluation, prompt management, experiments and human annotation. Every product feature is MIT licensed, with self-hosting via Docker Compose, Kubernetes or Terraform alongside a managed cloud in US and EU regions.
- MIT licensing across all product features rather than an open-core tease
- Hierarchical traces are the right shape for debugging agents, not just calls
- All three evaluation methods in one place, which makes calibration possible
- Self-host or managed cloud, with EU and US regions and a HIPAA-ready option
- SDK instrumentation means coverage is only as good as the code you write
- Self-hosting is insurance rather than a plan for most teams, and carries real operational cost
- No operating company, headquarters or size is stated on the site
Which Should You Choose?
Choose Helicone if…
- you want request logging across every major LLM provider
- a free or freemium plan is important
Choose Langfuse if…
- you want hierarchical tracing across model calls, tool invocations and retrieval steps
- a free or freemium plan is important
Helicone vs Langfuse: The Verdict
Your use case decides this one: Helicone leans into request logging across every major LLM provider, while Langfuse is built for hierarchical tracing across model calls, tool invocations and retrieval steps. Weigh features and pricing for your workflow. Both have a free or freemium tier, so spin up each and keep the one that clicks.
Frequently Asked Questions
Is Helicone better than Langfuse?
Neither is universally better — it depends on your budget and which features matter most. The side-by-side breakdown above shows where each one wins.
What is the difference between Helicone and Langfuse?
Helicone (freemium) is best for request logging across every major LLM provider, while Langfuse (freemium) is best for hierarchical tracing across model calls, tool invocations and retrieval steps. See the full feature and pricing comparison above.
Is Helicone or Langfuse cheaper?
Both have paid plans — pricing depends on your usage tier. Open each tool's review for current prices, and watch for free trials.
Which is better for beginners, Helicone or Langfuse?
Helicone is usually the easier starting point thanks to a lower barrier to entry. Beginners should favour a free tier and a simple interface over raw power.
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About the Authors
AI Tools Comparison Analyst
Olivia runs side-by-side comparisons and benchmarks, digging into pricing, features, and real-world performance so readers can choose between competing AI tools with confidence.
Senior AI Tools Reviewer
Daniel reviews AI tools the slow way — by actually using them on real projects. His reviews cover what works, what breaks, and who each tool is genuinely a good fit for.
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Last updated October 2026. Comparisons are ranked by our Editor Score (features, value and pricing, blended with verified user reviews where a tool has them) — see our methodology.