--- title: "athina-evals vs auto-evaluator" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/athina-ai-athina-evals-vs-langchain-ai-auto-evaluator" tools: ["athina-ai-athina-evals", "langchain-ai-auto-evaluator"] --- # athina-evals vs auto-evaluator *GraphCanon updated Aug 8, 2026* ## Verdict Pick athina-evals when athina-evals is primarily Python; auto-evaluator is TypeScript; pick auto-evaluator when auto-evaluator is primarily TypeScript; athina-evals is Python. [athina-evals](https://docs.athina.ai) reports 301 GitHub stars, 22 forks, and 3 open issues, last pushed Jun 6, 2025. [auto-evaluator](https://autoevaluator.langchain.com/) has 783 stars, 102 forks, and 21 open issues, last pushed Jun 26, 2025. Figures are from public GitHub metadata via [athina-evals's repository](https://github.com/athina-ai/athina-evals) and [auto-evaluator's repository](https://github.com/langchain-ai/auto-evaluator). | | [athina-evals](/tools/athina-ai-athina-evals.md) | [auto-evaluator](/tools/langchain-ai-auto-evaluator.md) | | --- | --- | --- | | Tagline | Python SDK for evaluating LLM generated responses | auto-evaluator | | Stars | 301 | 783 | | Forks | 22 | 102 | | Open issues | 3 | 21 | | Language | Python | TypeScript | | Adopt for | athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks. | - | | Persona | - | - | | Runtime | - | - | | License | - | Other | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [athina-evals](/tools/athina-ai-athina-evals.md) | [auto-evaluator](/tools/langchain-ai-auto-evaluator.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Archived (8%) | | Days since push | 417d | 408d | | Archived on GitHub | No | Yes | | Open issues (now) | 3 | 21 | | Full report | [trust report](/tools/athina-ai-athina-evals/trust.md) | [trust report](/tools/langchain-ai-auto-evaluator/trust.md) | ## Decision facts: athina-evals - **Adopt for:** athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks. ## Choose when ### Choose athina-evals if… - athina-evals is primarily Python; auto-evaluator is TypeScript. - Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval. - When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics ### Choose auto-evaluator if… - auto-evaluator is primarily TypeScript; athina-evals is Python. - Tags unique to auto-evaluator: auto-evaluation, railway, typescript, vercel. - Use auto-evaluator when you are working with TypeScript and need an integrated solution for evaluating AI models ## When NOT to use athina-evals - If open-source alternatives with transparent customization options are preferred over athina-evals' approach - In scenarios where API access requirements limit the ability to perform evaluations offline or in private environments ## When NOT to use auto-evaluator - Avoid using auto-evaluator if you require a multi-language support environment, as it focuses solely on TypeScript - Do not use this tool if your project's hosting requirements do not align with using Vercel or Railway ## Common questions ### What is the difference between athina-evals and auto-evaluator? athina-evals: Python SDK for evaluating LLM generated responses. auto-evaluator: auto-evaluator. See the comparison table for live GitHub stats and shared categories. ### When should I choose athina-evals over auto-evaluator? Choose athina-evals over auto-evaluator when athina-evals is primarily Python; auto-evaluator is TypeScript; Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval; When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics. ### When should I choose auto-evaluator over athina-evals? Choose auto-evaluator over athina-evals when auto-evaluator is primarily TypeScript; athina-evals is Python; Tags unique to auto-evaluator: auto-evaluation, railway, typescript, vercel; Use auto-evaluator when you are working with TypeScript and need an integrated solution for evaluating AI models. ### When should I avoid athina-evals? If open-source alternatives with transparent customization options are preferred over athina-evals' approach In scenarios where API access requirements limit the ability to perform evaluations offline or in private environments ### When should I avoid auto-evaluator? Avoid using auto-evaluator if you require a multi-language support environment, as it focuses solely on TypeScript Do not use this tool if your project's hosting requirements do not align with using Vercel or Railway ### Is athina-evals or auto-evaluator more popular on GitHub? auto-evaluator has more GitHub stars (783 vs 301). Stars measure visibility, not whether either tool fits your constraints. ### Are athina-evals and auto-evaluator open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to athina-evals or auto-evaluator? GraphCanon lists graph-backed alternatives at [athina-evals alternatives](/tools/athina-ai-athina-evals/alternatives) and [auto-evaluator alternatives](/tools/langchain-ai-auto-evaluator/alternatives) ([athina-evals markdown twin](/tools/athina-ai-athina-evals/alternatives.md), [auto-evaluator markdown twin](/tools/langchain-ai-auto-evaluator/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/athina-ai-athina-evals-vs-langchain-ai-auto-evaluator.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, athina-evals or auto-evaluator? athina-evals: Dormant. auto-evaluator: Archived. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for athina-evals and auto-evaluator? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [athina-evals trust report](/tools/athina-ai-athina-evals/trust); [auto-evaluator trust report](/tools/langchain-ai-auto-evaluator/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=athina-ai-athina-evals`](/api/graphcanon/graph?tool=athina-ai-athina-evals) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_