Langfuse

What Langfuse helps you do

Langfuse records LLM traces, manages prompt versions and supports evaluations. It suits application teams who need to understand token cost and output changes across a release.

Best for: Open-source LLM observability and prompt versions.

A small task to try

1. Instrument a synthetic help-desk request with the SDK
2. Give the prompt an explicit version label
3. Run a normal and an unanswered question
4. Review the trace, token use and output score before changing production

Illustrative input: Compare prompt v1 and v2 on: Can I return an item after 14 days? Source allows 14 days only.

Illustrative expected result: A labelled comparison that flags unsupported exceptions rather than rewarding a longer answer. This is an editorial example, not a recorded vendor test. Check it against your original material before using it.

Access and buying guidance

Cloud Hobby is free with 50,000 units/month and 30-day historical access, no card required. Higher tiers and self-hosted enterprise features have separate terms; model API use is not included.

A trace can contain user content, so retention and access need planning. Start with the smallest useful task; keep the original input and compare the result before committing to a larger workflow.

Alternatives for a different workflow

Dify: use built-in app run history. Langflow: explore visual application flow design.

Sources and review

Reviewed 9 October 2026 against official product documentation and official pricing / access terms. Feature access and prices can change; the linked provider terms govern your account.