Pydantic Logfire vs Galileo

Both are observability & tracing tools. Here is how they actually differ on price, billing model and deployment.

Pydantic Logfire Galileo
Category Observability & Tracing Observability & Tracing
Our rating 5/5 4/5
Starting price $49/mo $100/mo
Billing meter record span
Free plan Yes Yes
Free self-hosting No or paid tier only No or paid tier only
Best for 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. Enterprise GenAI teams that have been burned by production hallucinations and want research-grade eval metrics plus guardrails, and can run a sales process

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 →

Our verdict on Galileo

Galileo is the best-funded and arguably most research-forward platform here, and the Luna eval models are a real bet on making evaluation cheap enough to run continuously. Two caveats. First, make sure you're evaluating this Galileo and not the design tool that shares the name - the pricing and reviews get conflated constantly. Second, above the $100 Pro tier everything is contact-sales, and self-host is Enterprise-only, so this is a platform you buy through a rep, not a card.

Full Galileo review →
These two meter differently, so published prices are not comparable. Model both against your own workload →

Frequently Asked Questions

What is the main difference between Pydantic Logfire and Galileo?

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. Galileo: Enterprise GenAI teams that have been burned by production hallucinations and want research-grade eval metrics plus guardrails, and can run a sales process Both sit in Observability & Tracing, so the decision usually comes down to billing model and deployment rather than raw capability.

Which is cheaper, Pydantic Logfire or Galileo?

It depends entirely on your workload shape, because they meter differently - Pydantic Logfire bills on record and Galileo bills on span. Published starting prices are $49/mo and $100/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 Pydantic Logfire or Galileo?

Pydantic Logfire: No or paid tier only. Galileo: No or paid tier only. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.