opik vs weave
LLM tracing and evaluation tools compared
opik and weave both trace and evaluate generative AI applications, helping developers investigate behavior and compare changes. opik covers a broader operational workflow with monitoring, integrations, and self-hosting options, while weave focuses on Python-based tracing and evaluations.
opik: Trace, Evaluate, and Monitor LLM Applications
Opik is Comet’s open-source platform for tracing, evaluating, and monitoring LLM applications, RAG systems, and AI agents. It combines framework integrations, datasets and experiments, prompt tools, and production dashboards, with cloud and self-hosted options.
weave: Trace and Evaluate Generative AI Applications
Weave helps developers trace language model inputs, outputs, and function calls, then organize and evaluate application runs. It suits teams building AI features that need debugging and repeatable comparisons across experiments and production.
| opik | weave | |
|---|---|---|
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Stars | 22.8k | 1.1k |
| Forks | 1.9k | 171 |
| Last analyzed | Oct 22, 2026 | Oct 3, 2026 |
Key differences
- opik captures traces across model calls, tools, retrieval, and agent workflows; weave traces decorated functions and related calls, including validation and data transformations.
- opik includes datasets, built-in evaluation metrics, production monitoring, prompt experiments, and CI/CD testing; weave focuses on tracing, structured evaluations, and organizing information across experimentation and production.
- opik offers Python and TypeScript SDKs, framework integrations, and OpenTelemetry support; weave integrates tracing into Python code with the `weave.op` decorator.
- opik can run locally, on a team's own infrastructure, or through Comet Cloud; weave requires Python 3.10 or higher and a Weights & Biases account.
- Both use the Apache-2.0 license. opik lists 22.4k stars and 1.8k forks, while weave lists 1.1k stars and 171 forks.
- opik supports self-hosting with Docker Compose and documents Kubernetes and Helm; weave's README says work on its engine and boards is paused while it focuses on tracing and evaluations.
Choose opik if you…
- need production monitoring alongside tracing and evaluation.
- want to assess RAG outputs with metrics such as relevance, context precision, or hallucination.
- need self-hosting options or CI/CD evaluation for an LLM pipeline.
Choose weave if you…
- want tracing integrated into Python code through a decorator.
- need to inspect nested calls, inputs, and outputs while debugging application behavior.
- want repeatable evaluations and tracing organized across experimentation and production.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.