agentevals vs langwatch
Open source tools for evaluating and monitoring AI agents
agentevals evaluates recorded OpenTelemetry traces, while langwatch combines evaluation and testing with production observability and broader LLM operations. The main distinction is focused, trace-based scoring versus a wider platform that also covers simulations, prompts, gateway workflows, and governance.
agentevals: Evaluate AI Agents from OpenTelemetry Traces
agentevals scores AI agent behavior from existing OpenTelemetry traces, without rerunning agents or making extra model calls. It suits teams building instrumented agents that need local evaluation, golden-set checks, or CI quality gates.
langwatch: Test and Monitor LLM Applications and AI Agents
LangWatch helps teams evaluate, test, and monitor LLM applications and AI agents in production. It combines observability, simulation testing, prompt management, an AI gateway, and governance, with cloud and self-hosted options.
| agentevals | langwatch | |
|---|---|---|
| Language | Python | TypeScript |
| License | Apache-2.0 | Apache-2.0 |
| Stars | 162 | 4.9k |
| Forks | 28 | 405 |
| Last analyzed | Oct 4, 2026 | Oct 3, 2026 |
Key differences
- agentevals scores existing Jaeger JSON or OTLP traces without rerunning agents; langwatch also offers simulation tests for evaluating or benchmarking agents.
- agentevals focuses on trace evaluation, including tool trajectories and response checks; langwatch spans observability, prompt management, an AI gateway, and governance.
- agentevals is written in Python; langwatch is written in TypeScript.
- Both list Apache-2.0 licensing, but langwatch notes that enterprise modules under `platform/app/ee/` require a commercial license for production use.
- agentevals supports offline CLI evaluation and a local UI, with basic evaluation not requiring a database; langwatch offers cloud and self-hosted options, with separate guidance for production self-hosting.
- agentevals warns that it is under active development and breaking changes may occur; langwatch describes a broader set of operational areas and advises teams to assess integrations and fit.
Choose agentevals if you…
- need to score existing OpenTelemetry traces without rerunning agents or making extra model calls.
- want offline CLI checks, golden evaluation sets, or CI gates based on recorded behavior.
- prefer a focused evaluation workflow with custom evaluators and local trace inspection.
Choose langwatch if you…
- need simulation testing alongside production observability for LLM applications or agents.
- want prompt management, an AI gateway with virtual keys and budgets, or governance workflows.
- need to inspect coding-agent sessions and analyze usage costs across teams or pull requests.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.