--- title: "simple-evals vs auto-evaluator" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openai-simple-evals-vs-rlancemartin-auto-evaluator" tools: ["openai-simple-evals", "rlancemartin-auto-evaluator"] --- # simple-evals vs auto-evaluator *GraphCanon updated Aug 8, 2026* ## Verdict Pick simple-evals if simple-evals provides lightweight tools for evaluating language models using reference implementations from HealthBench, BrowseComp, SimpleQA. Last updates July 2025; 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 using configurations chosen via UI. [simple-evals](https://github.com/openai/simple-evals) reports 4.6k GitHub stars, 501 forks, and 56 open issues, last pushed Apr 22, 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 [simple-evals's repository](https://github.com/openai/simple-evals) and [auto-evaluator's repository](https://github.com/rlancemartin/auto-evaluator). | | [simple-evals](/tools/openai-simple-evals.md) | [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) | | --- | --- | --- | | Tagline | A lightweight library for evaluating language models. | A lightweight evaluation tool for question-answering using Langchain | | Stars | 4,595 | 1,105 | | Forks | 501 | 92 | | Open issues | 56 | 3 | | Language | Python | Python | | Adopt for | simple-evals provides lightweight tools for evaluating language models using reference implementations from HealthBench, BrowseComp, SimpleQA. Last updates July 2025. | 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 | MIT licensed Python library for transparent language model evaluations with specific benchmark support until July 2025. | - | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [simple-evals](/tools/openai-simple-evals.md) | [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 106d | 1186d | | Open issues (now) | 56 | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/openai-simple-evals/trust.md) | [trust report](/tools/rlancemartin-auto-evaluator/trust.md) | ## Decision facts: simple-evals - **Adopt for:** simple-evals provides lightweight tools for evaluating language models using reference implementations from HealthBench, BrowseComp, SimpleQA. Last updates July 2025. - **License detail:** MIT licensed Python library for transparent language model evaluations with specific benchmark support until July 2025. ## 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 simple-evals if… - Tags unique to simple-evals: benchmark, depreciation notice, language-models. - When you need a stable baseline to evaluate model performance with specific benchmarks like MMLU, HumanEval, and DROP that won't change after July 2025 - More GitHub stars (4.6k vs 1.1k) - visibility, not fit. ### Choose auto-evaluator if… - Tags unique to auto-evaluator: gpt-3.5-turbo, langchain, llm, question-answering. - Use when you need a lightweight solution for testing question-answering capabilities of Langchain models. - Leaner open-issue backlog (3). ## When NOT to use simple-evals - For evaluating models released or significantly updated after July 2025, as this tool does not include future benchmarks - When you need a tool that will adapt and expand its benchmark set with emerging model releases and evaluation tasks beyond 2025 ## 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 simple-evals and auto-evaluator? simple-evals: A lightweight library for evaluating language models.. 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 simple-evals over auto-evaluator? Choose simple-evals over auto-evaluator when Tags unique to simple-evals: benchmark, depreciation notice, language-models; When you need a stable baseline to evaluate model performance with specific benchmarks like MMLU, HumanEval, and DROP that won't change after July 2025; More GitHub stars (4.6k vs 1.1k) - visibility, not fit. ### When should I choose auto-evaluator over simple-evals? Choose auto-evaluator over simple-evals when Tags unique to auto-evaluator: gpt-3.5-turbo, langchain, llm, question-answering; Use when you need a lightweight solution for testing question-answering capabilities of Langchain models; Leaner open-issue backlog (3). ### When should I avoid simple-evals? For evaluating models released or significantly updated after July 2025, as this tool does not include future benchmarks When you need a tool that will adapt and expand its benchmark set with emerging model releases and evaluation tasks beyond 2025 ### 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 simple-evals or auto-evaluator more popular on GitHub? simple-evals has more GitHub stars (4,595 vs 1,105). Stars measure visibility, not whether either tool fits your constraints. ### Are simple-evals and auto-evaluator open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to simple-evals or auto-evaluator? GraphCanon lists graph-backed alternatives at [simple-evals alternatives](/tools/openai-simple-evals/alternatives) and [auto-evaluator alternatives](/tools/rlancemartin-auto-evaluator/alternatives) ([simple-evals markdown twin](/tools/openai-simple-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-simple-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, simple-evals or auto-evaluator? simple-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 simple-evals and auto-evaluator? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [simple-evals trust report](/tools/openai-simple-evals/trust); [auto-evaluator trust report](/tools/rlancemartin-auto-evaluator/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=openai-simple-evals`](/api/graphcanon/graph?tool=openai-simple-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/_