helicone vs langfuse

Common questions

What is the difference between helicone and langfuse?

helicone: Open source LLM observability platform. langfuse: Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. See the comparison table for live GitHub stats and shared categories.

When should I choose helicone over langfuse?

Choose helicone over langfuse when License: helicone is Apache-2.0, langfuse is Other; Both Helicone and Langfuse are observability platforms for AI/LLMs providing evaluation, metrics, and monitoring; Tags unique to helicone: agent-monitoring, gpt, langchain, llm-cost; Use Helicone when you need an open-source solution that can monitor a wide range of LLMs, including more than 100 available through one API.

When should I choose langfuse over helicone?

Choose langfuse over helicone when License: langfuse is Other, helicone is Apache-2.0; Pricing: Langfuse offers an open-source version under MIT license except for some 'ee' folders, indicating a possible enterprise edition. Specific pricing details are not provided within the repository content; Requirements: Requires Docker; Self-hosting options include Docker Compose and Kubernetes for deployment.; Both Helicone and Langfuse are observability platforms for AI/LLMs providing evaluation, metrics, and monitoring; Tags unique to langfuse: observability, open-source, prompt management, self-hosted; Use Langfuse if you need advanced prompt management tools, as it offers comprehensive features specifically tailored for managing prompts efficiently.

When should I avoid helicone?

Do not use Helicone if you have strict data privacy needs that are better served by fully localized or proprietary observability solutions. Avoid using this platform if your project specifically requires real-time integration with a specific model outside of Helicone's extensive but curated list.

When should I avoid langfuse?

Avoid using Langfuse if you prefer a vendor-managed service as it requires self-hosting. This can be less desirable for teams looking to minimize infrastructure management. If your development environment is not compatible with Kubernetes, Docker Compose configurations, or major cloud providers (AWS, Azure, GCP) that Langfuse supports via specific templates and Helm, it may not be the optimal choice.

Is helicone or langfuse more popular on GitHub?

langfuse has more GitHub stars (32,271 vs 6,073). Stars measure visibility, not whether either tool fits your constraints.

Are helicone and langfuse open source?

Yes - both are open-source projects on GitHub (helicone: Apache-2.0, langfuse: Other).

Where can I find alternatives to helicone or langfuse?

GraphCanon lists graph-backed alternatives at helicone alternatives and langfuse alternatives (helicone markdown twin, langfuse markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, helicone or langfuse?

helicone: Very active. langfuse: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for helicone and langfuse?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: helicone trust report; langfuse trust report.