Helicone vs Langfuse
Two of the most-asked-about agents in the developer-tools space. Here's how they actually stack up.
Helicone
LLM observability and cost monitoring for production AI applications
Free tier
Read full review →Langfuse
Open-source LLM observability with full self-hosting and production-ready tracing
Free tier
Read full review →Side-by-side comparison
| Helicone | Langfuse | |
|---|---|---|
| Tagline | LLM observability and cost monitoring for production AI applications | Open-source LLM observability with full self-hosting and production-ready tracing |
| Pricing | Free tier | Free tier |
| Categories | developer-tools, api, productivity | developer-tools, open-source, api |
| Made by | Helicone | Langfuse |
| Launched | 2023-06 | 2023-07 |
| Platforms | Web, API | Web, API, Self-hosted |
| Status | active | active |
Helicone highlights
- + One-line integration via proxy URL change, no SDK required
- + Real-time cost tracking per model, user, and custom property
- + Request and response logging with full prompt and output capture
- + Latency monitoring and percentile breakdowns by model and endpoint
- + User segmentation: track costs and usage per end-user or organization
Langfuse highlights
- + Full trace and span logging for any LLM framework or direct API calls
- + Self-hosting via Docker Compose or Kubernetes: own your data completely
- + Prompt management with versioning, tags, and production/staging environments
- + Dataset and evaluation system: run evals on curated test sets
- + Score collection for human feedback and LLM-as-judge evaluation
Frequently Asked Questions
Which is better, Helicone or Langfuse?
Neither is universally better. Helicone (Free tier) leans into developer-tools, while Langfuse (Free tier) is closer to developer-tools. Pick based on which workflow you actually do every day.
What is the price difference between Helicone and Langfuse?
Helicone is free tier. Langfuse is free tier. See the pricing row in the comparison table.
Can I use Helicone and Langfuse together?
In most cases, yes. They serve overlapping but distinct needs, so running them side by side is common until you decide which fits your workflow.