MLflow GenAI Evaluation vs Opik

MLflow GenAI Evaluation is a free, open-source API and UI for measuring, improving, and monitoring LLM applications and AI agents from development through production. Evaluation Datasets centralize test cases, expected answers, and evaluation data. Teams can collect feedback from end users and domain experts, attach it to traces, and retain metadata. Scoring includes LLM-as-a-Judge, custom LLM judges, and code-based scorers; automatic evaluation supports LLM judges but not code-based scorers. Results appear in the MLflow UI with per-record details and comparisons between agent versions. MLflow Tracing records production metrics such as latency and token usage. Integrations are listed for more than 40 LLM and agent libraries and frameworks, including OpenTelemetry, LangChain, OpenAI, and Anthropic. Judge adapters include Anthropic, Bedrock, Google, and xAI. API, self-hosted, and web options are available, with Python SDK support, prompt history and testing, regression runs, safety evaluations, tool-call checks, deployment controls, and optional basic HTTP authentication.

Opik helps teams building applications or agents that call an LLM log actions and evaluate behavior across development, testing, and production. It captures and visualizes traces, supports annotation, and provides audit logs. Its evaluation tools include more than 30 metrics for outcomes such as answer relevance, context precision, task completion, and hallucination. In production, Opik can evaluate traces in real time, alert when criteria fail, and track token use and model costs. Test Suites offer pass/fail assertions, an Agent Playground supports end-to-end tests, and a Prompt Optimizer provides six algorithms. Core observability and evaluation features are available as open-source code for local use. Opik includes a REST API and Python client, with Python and TypeScript SDKs listed, and integrations with more than 40 frameworks, model providers, and gateways. Free Cloud allows up to 10 team members, 25,000 spans per month, and 60-day retention. Pro Cloud costs $19 a month and lists up to 50 team members and 100,000 spans monthly.