What is the main difference between Helicone and Langfuse?

Helicone and Langfuse are both llm observability & evaluation but differ in their approach, features, and target audience. Compare their GitHub stats, technology stack, and community adoption to make the best choice.

Which is better: Helicone or Langfuse?

The choice between Helicone and Langfuse depends on your specific needs, technical requirements, and team preferences. Both are quality open source solutions with active communities.

Can I migrate from Helicone to Langfuse?

Migration between Helicone and Langfuse is possible but requires careful planning. Consider data export/import capabilities, feature parity, and potential workflow changes.

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Helicone vs Langfuse

Learn how Helicone and Langfuse differ in their key features, development activity, technology stack and community adoption, so you can decide which of these llm observability & evaluation is best for you.

Helicone

Open-source platform for logging, monitoring, and debugging LLM applications. Route, debug, and analyze AI apps with comprehensive observability tools.

Visit Helicone Read more

6,148stars+90(+1.5%)

Last 30 days

Last commit
11 hours ago
Repository age
4 years
Version
v2025.08.21-1
License
Apache-2.0
Repository
helicone/helicone

Langfuse

Langfuse provides tracing, evaluations, prompt management, and analytics to debug and improve LLM applications.

Visit Langfuse Read more

34,481stars+1,507(+4.6%)

Last 30 days

Last commit
9 hours ago
Repository age
3 years
Version
v4.35.0
License
MIT
Self-hosted
Yes
Repository
langfuse/langfuse

Detailed Comparison

Langfuse appears to have several advantages over Helicone, particularly in popularity, growth, licensing and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.

Langfuse wins

Community & Popularity

Langfuse significantly outpaces Helicone in community adoption with 34,481 stars compared to 6,148 stars on GitHub. This 5.6x difference suggests Langfuse has a much larger and more active community. In terms of developer contributions, Langfuse has 3,757 forks, indicating strong developer engagement.

Langfuse wins

Growth Momentum

Langfuse is growing faster, adding 1,507 stars in the last 30 days (+4.6%) against adding 90 stars for Helicone (+1.5%). Langfuse is both larger and pulling further ahead.

Comparable

Development Activity

Both projects show recent activity, with Helicone last updated 11 hours ago and Langfuse 9 hours ago.

Comparable

Technology Stack

Both tools share common technology foundations, being built with JavaScript, CSS, Bash, Typescript, JSX, Next.js. However, they differ in their additional technology choices: Helicone uses Python.

Comparable

Project Maturity

Both projects started around the same time, with Helicone beginning 4 years ago and Langfuse 3 years ago.

Langfuse wins

Licensing

Langfuse uses the MIT license, which is more permissive than Helicone's Apache-2.0 license, potentially offering greater flexibility for commercial use and integration.

Comparable

Use Cases & Features

Both tools serve similar use cases in LLM Observability & Evaluation.

Langfuse wins

Hosting & Deployment

Langfuse provides self-hosting options for complete data control and customization, while Helicone may be primarily cloud-based or require different deployment approaches.