Langfuse vs Pydantic Logfire
Both are observability & tracing tools. Here is how they actually differ on price, billing model and deployment.
Langfuse
The open-source LLM observability default. Free, MIT-licensed, genuinely feature-complete when self-hosted - now a ClickHouse subsidiary after its January 2026 acquisition.
Pydantic Logfire
OpenTelemetry-native observability from the Pydantic team, and the cheapest credible option in the category at $2 per million records with 10M free every month. The catch is that metrics count as records, and common integrations emit them silently.
| Langfuse | Pydantic Logfire | |
|---|---|---|
| Category | Observability & Tracing | Observability & Tracing |
| Our rating | 5/5 | 5/5 |
| Starting price | $29/mo | $49/mo |
| Billing meter | event | record |
| Free plan | Yes | Yes |
| Free self-hosting | Yes, free | No or paid tier only |
| Best for | Teams that want an open-source observability platform they can self-host without losing features | Teams that want one observability tool for their whole application rather than an LLM-specific silo, are comfortable on OpenTelemetry, and care about predictable, genuinely low cost. Especially strong for Python shops already using Pydantic or Pydantic AI. |
Our verdict on Langfuse
The open-source default for good reason - self-hosting is free and doesn't cripple the product, and it's dramatically cheaper than LangSmith at scale. The catch is operational, not commercial - the v3 architecture is four services now, and the migration bites. If you have the ops capacity, nothing else in the category gives you this much for free.
Full Langfuse review →Our verdict on Pydantic Logfire
Logfire is the best value in this category and it is not close. Ten million free records a month, then $2 per million, with no metering on seats, hosts or projects. The free tier hard-caps rather than billing you, which means a runaway instrumentation loop pauses ingestion instead of generating a five-figure invoice - a design decision almost nobody else in observability makes. It is full-stack OpenTelemetry rather than an LLM silo, so the database query that made your agent slow appears in the same trace as the LLM call, and you can query all of it with PostgreSQL-compatible SQL. The one real trap is the billing unit. Logfire bills records, and records include metrics, and integrations like httpx, SQLAlchemy and FastAPI emit aggregate metrics under the hood whether you asked for them or not. Teams get surprised by this. Turn off auto-emitted metrics you do not need and the economics are excellent.
Full Pydantic Logfire review →Frequently Asked Questions
What is the main difference between Langfuse and Pydantic Logfire?
Langfuse: Teams that want an open-source observability platform they can self-host without losing features Pydantic Logfire: Teams that want one observability tool for their whole application rather than an LLM-specific silo, are comfortable on OpenTelemetry, and care about predictable, genuinely low cost. Especially strong for Python shops already using Pydantic or Pydantic AI. Both sit in Observability & Tracing, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, Langfuse or Pydantic Logfire?
It depends entirely on your workload shape, because they meter differently - Langfuse bills on event and Pydantic Logfire bills on record. Published starting prices are $29/mo and $49/mo respectively, but those numbers are not comparable until you apply them to the same traffic. Use our cost calculator to model both against your own request volume and span count.
Can I self-host Langfuse or Pydantic Logfire?
Langfuse: Yes, free. Pydantic Logfire: No or paid tier only. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.