Both trace agents, run offline and online evals and version prompts. Logfire traces the whole application in one OpenTelemetry view and suits Python teams, especially on Pydantic AI; Opik is an open-source platform focused on LLM and agent evaluation that you can run yourself for free. Scope and licence separate them more than any single feature.[1][4]
Logfire is an OpenTelemetry observability platform for your whole application, LLM and agent calls included, from the team behind Pydantic; Opik is an LLM and agent tracing and evaluation platform from Comet. Opik's platform is Apache-2.0 and free to self-host. Logfire's platform is closed source, its SDKs and eval library are MIT, and self-hosting is Enterprise only.
| Decision factor | Logfire | Opik |
|---|---|---|
| Ownership | Pydantic, independent; Sequoia led its $12.5M Series A in 2024 | Comet ML, independent; reports $70M in total funding |
| Scope | Whole-application traces, logs and metrics, with Agents and LLMs views | LLM and agent tracing, evaluation and monitoring |
| Licence | Platform closed source; SDKs, pydantic-evals and Pydantic AI are MIT | Apache-2.0 for the core platform |
| Self-hosting | Enterprise only, on Kubernetes via Helm | Free; Kubernetes for production; user administration excluded |
| Online evals | Run inside your application via pydantic-evals, sampled, after the call | Rules in the platform score sampled traces, spans and threads |
| Run-time checks | AI gateway guardrails and spend caps on model calls routed through it | Guardrails your code calls; a failed check raises an exception |
| Free tier | Personal: 10M records a month, 1 seat, 30-day retention | Free Cloud: 25k spans a month, 10 members, 60-day retention |
| First paid tier | Team: $49 a month, 10M records, 5 seats | Pro Cloud: $19 a month, 100k spans, up to 50 members |
| Capability | Logfire | Opik | Prefactor |
|---|---|---|---|
| Observe | |||
| LLM call tracing | ✓ | ✓ | ✓ |
| Multi-step agent tracing (tool calls, nested spans) | ✓ | ✓ | ✓ |
| Cost tracking | ✓ | ✓ | ✓ |
| OpenTelemetry support | ✓ | ✓ | ✓ |
| Evaluate | |||
| Offline evals (datasets, experiments) | ✓ | ✓ | ✓ |
| Online evals on production traffic | ✓ | ✓ | ✓ |
| LLM-as-a-judge scoring | ✓ | ✓ | ✓ |
| Code-based evaluators | ✓ | ✓ | ✓ |
| Human review and annotation | Partial | ✓ | ✓ |
| Prompt versioning and playground | ✓ | ✓ | — |
| Act on findings | |||
| Runtime controls on live agent actions | Partial | Partial | ✓ |
| Gateway or proxy in the request path | ✓ | Partial | — |
| Licence and deployment | |||
| Open source | Partial | ✓ | Partial |
| Self-hosting | Partial | ✓ | Partial |
Logfire is built on OpenTelemetry and traces agent runs, tool calls and retrieval next to the application's HTTP and database spans. Its SDKs are thin OTel wrappers, so any standard OpenTelemetry SDK, in Go, Java, .NET or Ruby, can send data. If you want one place to see a slow database query and the agent step that triggered it, that is Logfire's design.
Opik is focused on the LLM and agent layer: traces of each agent step with thread grouping, more than 30 built-in judge metrics, an 'Agent as a Judge' that reads traces with tools, and Ollie, an assistant that analyses traces and writes fixes with test cases. It accepts OTLP over HTTP but does not set out to replace your application monitoring.
Logfire also covers more of the request path. The Pydantic AI Gateway was folded into Logfire in March 2026 and gives one key for several providers, with failover, weighted load balancing and spend caps. Opik's own gateway is in beta and documented for development and testing; for production it integrates with third-party gateways such as LiteLLM, Portkey and OpenRouter. Logfire's MCP server lets coding agents query production traces.
Opik's core platform is Apache-2.0 and self-hosted Opik has every feature except user administration. Comet describes the local Docker install as not production-ready and documents Kubernetes for production.
Logfire's server is closed source. Its Python, JavaScript and Rust SDKs, the pydantic-evals library and Pydantic AI are MIT-licensed, so your instrumentation and eval code are open even if the backend is not. Self-hosting Logfire is offered only on the Enterprise plan, on Kubernetes with PostgreSQL 16 or later and object storage. A dedicated single-tenant cloud in any GCP region is the other Enterprise option.
Logfire's Live Evaluations run in your own application. Evaluators from pydantic-evals score production calls in the background at a sample rate you set and send the results to Logfire as OpenTelemetry events. They score after the call and do not alter outputs. Human review is newer: run annotations are in beta and annotation queues are early access, and annotations do not feed eval aggregates.
Opik's online evaluation rules run in the platform and score sampled production traces, spans and threads, including custom Python metrics. Its annotation queues have been available longer, and since October 2026 they can fill automatically from feedback-score conditions.
Both add partial run-time checks. Logfire's AI gateway, folded into Logfire in March 2026, can observe, flag, redact or block prompts and completions and stop requests once a spend cap is reached, for model calls routed through it. Opik's guardrails are a blocking call your code makes; PII and topic checks are English only. Neither documents approvals on agent tool actions.
Opik also lets you cap judge spend per evaluation, a control added in July 2026.
As of 20 October 2026, Logfire bills on records, which include spans, logs and metrics. Personal is free with 10M records a month for one seat, and ingestion pauses at the cap. Team is $49 a month with 10M records and five seats ($25 per extra seat), Growth is $249 a month with unlimited seats, and extra records cost $2 per million on paid plans.
Opik bills on spans. Free Cloud includes 25k spans a month for up to 10 members; Pro Cloud is $19 a month for 100k spans and up to 50 members, then $5 per 100k. Self-hosted Opik has no span limit. Because Logfire counts every record from your application, not only LLM spans, compare on your real telemetry volume using Logfire's pricing and Opik's pricing.
Above the self-serve tiers, Logfire's Growth plan includes a boilerplate HIPAA BAA, and Enterprise adds SSO, SCIM and the self-hosted option. Opik's Enterprise plan adds unlimited users, SSO and on-premises or fully hosted deployment.
We sell the layer this section describes. Read it with that in mind.
Stated plainly, since Prefactor publishes this page: Prefactor is an agent evaluation platform that scores each step of a run and acts on what it finds through runtime policies on tool calls and data access, approval holds for risky actions, and a kill switch for a run, an agent or a team. Logfire's gateway checks model calls routed through it and Opik's guardrails run where your code calls them; neither holds an agent's tool action for approval. Prefactor has no prompt playground or prompt registry and its platform is hosted, so for whole-application tracing Logfire fits better, and for free self-hosting Opik does. See the full comparison of 15 platforms.
Reviewed against public product and documentation pages on October 20, 2026. If a vendor has changed a feature, product name, or positioning since then, send a correction and we will update it. Numbered source links in the page body point to the ordered sources below.
Prefactor scores each step of every agent run and can hold or stop an action when a score says it should not happen. Start on the free tier: 5,000 spans a month, no credit card required.
Prefactor helps teams observe, evaluate, and improve their AI agents in production, across every framework and provider.