--- title: "evals vs auto-evaluator" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openai-evals-vs-rlancemartin-auto-evaluator" tools: ["openai-evals", "rlancemartin-auto-evaluator"] --- # evals vs auto-evaluator *GraphCanon updated Aug 8, 2026* ## Verdict Pick evals if evals is an evaluation framework from OpenAI for assessing large language models and systems built with them. It includes an open-source registry of benchmarks and tools to create custom evaluations; pick auto-evaluator if auto-evaluator is a Python-based tool designed for evaluating LLM QA chains with the capability to auto-generate question-answer pairs from user-provided documents and evaluate answers. [evals](https://github.com/openai/evals) reports 19k GitHub stars, 3.0k forks, and 213 open issues, last pushed Apr 14, 2026. [auto-evaluator](https://autoevaluator.langchain.com/) has 1.1k stars, 92 forks, and 3 open issues, last pushed May 10, 2023. Figures are from public GitHub metadata via [evals's repository](https://github.com/openai/evals) and [auto-evaluator's repository](https://github.com/rlancemartin/auto-evaluator). | | [evals](/tools/openai-evals.md) | [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) | | --- | --- | --- | | Tagline | Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks. | A lightweight evaluation tool for question-answering using Langchain | | Stars | 19,127 | 1,105 | | Forks | 3,050 | 92 | | Open issues | 213 | 3 | | Language | Python | Python | | Adopt for | Evals is an evaluation framework from OpenAI for assessing large language models and systems built with them. It includes an open-source registry of benchmarks and tools to create custom evaluations. | Auto-evaluator is a Python-based tool designed for evaluating LLM QA chains with the capability to auto-generate question-answer pairs from user-provided documents and evaluate answers using configurations chosen via UI. | | Persona | - | - | | Runtime | - | - | | License | Other | - | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [evals](/tools/openai-evals.md) | [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 115d | 1186d | | Open issues (now) | 213 | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/openai-evals/trust.md) | [trust report](/tools/rlancemartin-auto-evaluator/trust.md) | ## Shared compatibility - **OpenAI API**: [evals](/tools/openai-evals.md) - OpenAI API; [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) - OpenAI API - **Python**: [evals](/tools/openai-evals.md) - Python runtime; [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) - Python runtime ## Decision facts: evals - **Adopt for:** Evals is an evaluation framework from OpenAI for assessing large language models and systems built with them. It includes an open-source registry of benchmarks and tools to create custom evaluations. ## Decision facts: auto-evaluator - **Adopt for:** Auto-evaluator is a Python-based tool designed for evaluating LLM QA chains with the capability to auto-generate question-answer pairs from user-provided documents and evaluate answers using configurations chosen via UI. ## Choose when ### Choose evals if… - Tags unique to evals: benchmarking, custom eval creation, evaluation-framework, large language models. - * When you need a comprehensive set of pre-existing evals and the ability to create your own tailored tests using specific use cases, especially within the OpenAI model ecosystem. - More GitHub stars (19k vs 1.1k) - visibility, not fit. ### Choose auto-evaluator if… - Tags unique to auto-evaluator: evaluation, gpt-3.5-turbo, langchain, llm. - Use when you need a lightweight solution for testing question-answering capabilities of Langchain models. - Leaner open-issue backlog (3). ## When NOT to use evals - * When evaluating models or systems that do not benefit from being integrated with the OpenAI API, as some features like direct evals configuration in the OpenAI Dashboard require an OpenAI key. - * If you are looking for an evaluation framework that doesn’t involve external dependencies such as Git Large File Storage (LFS) and specific Python version requirements (Python 3.9 minimum), or if a ## When NOT to use auto-evaluator - Avoid using this tool when you do not have access to an OpenAI API key providing access to GPT-4, as it uses that by default for optimal settings. - If you are looking for a tool that does not require you to input documents for question generation and prefer a more customized prompt approach rather than the auto-generation feature. ## Common questions ### What is the difference between evals and auto-evaluator? evals: Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks.. auto-evaluator: A lightweight evaluation tool for question-answering using Langchain. See the comparison table for live GitHub stats and shared categories. ### When should I choose evals over auto-evaluator? Choose evals over auto-evaluator when Tags unique to evals: benchmarking, custom eval creation, evaluation-framework, large language models; * When you need a comprehensive set of pre-existing evals and the ability to create your own tailored tests using specific use cases, especially within the OpenAI model ecosystem; More GitHub stars (19k vs 1.1k) - visibility, not fit. ### When should I choose auto-evaluator over evals? Choose auto-evaluator over evals when Tags unique to auto-evaluator: evaluation, gpt-3.5-turbo, langchain, llm; Use when you need a lightweight solution for testing question-answering capabilities of Langchain models; Leaner open-issue backlog (3). ### When should I avoid evals? * When evaluating models or systems that do not benefit from being integrated with the OpenAI API, as some features like direct evals configuration in the OpenAI Dashboard require an OpenAI key. * If you are looking for an evaluation framework that doesn’t involve external dependencies such as Git Large File Storage (LFS) and specific Python version requirements (Python 3.9 minimum), or if a ### When should I avoid auto-evaluator? Avoid using this tool when you do not have access to an OpenAI API key providing access to GPT-4, as it uses that by default for optimal settings. If you are looking for a tool that does not require you to input documents for question generation and prefer a more customized prompt approach rather than the auto-generation feature. ### Is evals or auto-evaluator more popular on GitHub? evals has more GitHub stars (19,127 vs 1,105). Stars measure visibility, not whether either tool fits your constraints. ### Are evals and auto-evaluator open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to evals or auto-evaluator? GraphCanon lists graph-backed alternatives at [evals alternatives](/tools/openai-evals/alternatives) and [auto-evaluator alternatives](/tools/rlancemartin-auto-evaluator/alternatives) ([evals markdown twin](/tools/openai-evals/alternatives.md), [auto-evaluator markdown twin](/tools/rlancemartin-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/openai-evals-vs-rlancemartin-auto-evaluator.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, evals or auto-evaluator? evals: Slowing. auto-evaluator: Dormant. 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 evals and auto-evaluator? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [evals trust report](/tools/openai-evals/trust); [auto-evaluator trust report](/tools/rlancemartin-auto-evaluator/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=openai-evals`](/api/graphcanon/graph?tool=openai-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/_