Metaflow vs Opik
Metaflow
metaflow.orgOpik
comet.comSide by side
| Figure | Metaflow | Opik |
|---|---|---|
| Price from | Free | $19/mo |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | Yes | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 4 |
| Spec score · MLOps Platforms | 8.6 (#4) | 8.9 (#2) |
| Integrations | Documented integrations include AWS Batch, AWS Step Functions, Kubernetes, Argo Workflows, and Apache Airflow. | The integration catalog covers TypeScript, Python, Java, .NET and Ruby ecosystems plus no-code tools and OpenTelemetry. |
| Rating on G2 | 4.5 out of 5 from 3 reviews | No rating; 0 reviews listed for Opik |
| Self-hosting | Scaling and production features require deployment into the customer’s cloud account or Kubernetes cluster using infrastructure templates. | Self-hosting exposes the full feature set but omits user-management features; local Docker installation is for getting started, while Kubernetes is the production deployment option. |
| Support | The documentation points users to the Metaflow Slack community for help. | The pricing page lists community and self-service support across plans, email support for Pro and Enterprise, and dedicated support and SLAs for Enterprise. |
| System requirements | The official package supports macOS and Linux; Windows users are directed to WSL rather than native support. | The documented local setup assumes Git and Docker; Linux, macOS and Windows installation scripts are provided. |
| What it does | Metaflow is a Python library for developing, deploying and operating data-intensive data-science, machine-learning and AI applications. | Opik records agent interactions, retrieval, tool calls and model responses, then evaluates and monitors them across development, testing and production. |
Plans
In their own words
Metaflow
Metaflow is a free, open-source Python library for developing, deploying, and operating data-intensive data science, machine learning, and AI applications. It automatically tracks flows, experiments, and artifacts, and supports local workflow construction and testing. For larger workloads, it can use compute in a customer’s cloud account or Kubernetes clusters. Documented integrations include AWS Batch, AWS Step Functions, Kubernetes, Argo Workflows, and Apache Airflow. Deployments can use AWS, Azure, Google Cloud, Kubernetes, or on-premises clusters; artifact storage options include AWS S3, Azure Blob Storage, and Google Cloud Storage. The Python package runs on macOS and Linux, while Metaflow Sandbox offers free browser access to cloud and Kubernetes stacks. The project is licensed under Apache License 2.0, and its own-cloud model can use existing infrastructure and security policies. A local-only setup does not support external compute scaling or production-grade deployments. Metaflow is aimed at data scientists and ML or AI engineers; its documentation says it offers little benefit for small notebook experiments without scaling, criticality, or complexity needs.
Opik
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.