Comet vs MLflow GenAI Evaluation

Comet offers two product families on one platform: Opik for observing and evaluating LLM applications and agents, and MLOps for machine-learning workflows. Opik traces execution paths such as context retrieval, model responses and tool calls. Its evaluation tools include test suites, datasets, experiments, LLM-as-a-judge and heuristic metrics. The product lists integrations with more than 40 AI frameworks, model providers and gateways, including LangChain, OpenAI, Google ADK, LangGraph and CrewAI; OpenTelemetry support covers tracking applications in Ruby, Java and other languages. MLOps provides experiment tracking, dataset management, a model registry and production monitoring. Opik's open-source version can be self-hosted, and Enterprise offers flexible deployment options. Free Cloud allows up to 10 team members, 25k spans per month and 60-day data retention. Pro Cloud costs $19 a month and allows up to 50 team members and 100k spans monthly, with the same retention period. MLOps Free is also listed, while MLOps Pro costs $19 per user/month. Enterprise pricing is custom. Comet lists community support for all plans, email support for paid cloud Pro and Enterprise, and dedicated support and SLAs for Enterprise.

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.