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Open-source LLM evaluation and observability framework: trace, evaluate, monitor, and improve LLM applications.
Open-source LLM evaluation and observability framework: trace, evaluate, monitor, and improve LLM applications.
Opik is the open-source LLM evaluation and observability tool from Comet, released under Apache 2.0. It exists because most teams building LLM apps end up reinventing the same instrumentation stack: trace every LLM call, score outputs, store prompts as first-class artifacts, run evaluation suites in CI, and detect regressions in production. Opik does all of that out of the box with a self-hostable backend and SDKs for Python, TypeScript, and Ruby. The core trace view captures every LLM call, tool call, and intermediate step in a tree, with token counts and costs attached. The evaluation framework lets you score outputs with code-based checks, heuristic metrics, or LLM-as-judge using a library of pre-built evaluators (hallucination, answer relevance, context recall, etc) plus custom ones. Prompts are versioned artifacts you can iterate on in a playground, deploy by name, and roll back. Production monitoring catches drift and quality regressions across deployments. Opik integrates with every popular framework: OpenAI, Anthropic, LangChain, LlamaIndex, LiteLLM, Haystack, CrewAI, AutoGen, DSPy, and others. There's a free hosted cloud at Comet, a self-hostable open-source backend, and Comet's commercial offering for teams that want managed Opik with SSO, RBAC, and longer retention.
Capture and inspect the steps involved in an LLM application request so teams can understand how prompts, model calls, and application logic contribute to outputs.
Use Case:
Debug why a RAG pipeline returned an incorrect answer by reviewing the application steps that led to the final response.
Use trace, evaluation, monitoring, and prompt-related workflows together to support iterative improvement of LLM-backed features.
Use Case:
Improve a customer support agent's response quality by comparing prompt changes against an evaluation dataset.
The supplied metadata identifies Opik as open source with an Apache-2 tag, which can help teams inspect, extend, or evaluate the tool before committing to a hosted workflow.
Use Case:
Assess whether an open-source observability framework fits internal engineering and governance requirements.
Run evaluation workflows, including test suites and assertions referenced in current plan inclusions, to help teams judge whether LLM outputs meet expected quality criteria.
Use Case:
Benchmark a new model version against a test set to measure quality changes before deploying.
Connect prompt changes with trace and evaluation results as part of an observability and evaluation workflow; the supplied metadata includes prompt management as a tag, but exact prompt-management UI details are not confirmed in the supplied scrape.
Use Case:
Track prompt changes alongside evaluation results to understand whether a prompt revision improved behavior.
Monitor LLM application behavior and quality signals over time, while defining the product-specific thresholds and criteria that matter for the application.
Use Case:
Identify and debug quality degradation in a production chatbot by reviewing observed traces and evaluation results.
Free (Apache 2.0)
Free
Paid (tiers on website)
Custom
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This record was last enriched on 2026-06-04. Current Comet pricing information verified on 2026-06-04 lists Opik Open Source at $0, Free Cloud at $0 with up to 10 team members, 25k spans per month, and 60-day retention, Pro Cloud at $19 per month with up to 50 team members, 100k spans per month, and 60-day retention, and Enterprise at a custom quote. No specific 2026 release notes, launch announcements, roadmap items, or newly added features were present in the supplied scraped website content. The current factual positioning remains that Opik by Comet is an open-source, freemium LLM observability and evaluation framework focused on tracing, evaluating, monitoring, prompt-related workflows, and improvement of LLM applications.
LLM Observability
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AI Monitoring
Open-source LLM observability and gateway platform offering one-line integration, request logging, prompt management, evals, and a multi-provider proxy.
AI Evaluation
Braintrust review 2026: unified evals, prompt workbench, observability, and AI proxy used by OpenAI, Stripe, Notion — features, pricing, pros, cons.
Pricing and features change often. If anything on this Opik by Comet page is wrong or missing, tell us and include a link to the source. We review every correction.