--- title: "evalplus vs auto-evaluator" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/evalplus-evalplus-vs-rlancemartin-auto-evaluator" tools: ["evalplus-evalplus", "rlancemartin-auto-evaluator"] --- # evalplus vs auto-evaluator *GraphCanon updated Aug 8, 2026* ## Verdict Pick evalplus if evalplus offers tools for rigorously benchmarking and evaluating large language models like GPT-4 and ChatGPT in synthesizing program code using Python under the Apache-2.0 license; 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. [evalplus](https://evalplus.github.io) reports 1.8k GitHub stars, 205 forks, and 71 open issues, last pushed Oct 2, 2025. [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 [evalplus's repository](https://github.com/evalplus/evalplus) and [auto-evaluator's repository](https://github.com/rlancemartin/auto-evaluator). | | [evalplus](/tools/evalplus-evalplus.md) | [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) | | --- | --- | --- | | Tagline | Rigorous evaluation of LLM-synthesized code | A lightweight evaluation tool for question-answering using Langchain | | Stars | 1,794 | 1,105 | | Forks | 205 | 92 | | Open issues | 71 | 3 | | Language | Python | Python | | Adopt for | evalplus offers tools for rigorously benchmarking and evaluating large language models like GPT-4 and ChatGPT in synthesizing program code using Python under the Apache-2.0 license. | 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 | Apache-2.0 | - | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [evalplus](/tools/evalplus-evalplus.md) | [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 306d | 1186d | | Open issues (now) | 71 | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/evalplus-evalplus/trust.md) | [trust report](/tools/rlancemartin-auto-evaluator/trust.md) | ## Shared compatibility - **Python**: [evalplus](/tools/evalplus-evalplus.md) - Python runtime; [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) - Python runtime ## Decision facts: evalplus - **Adopt for:** evalplus offers tools for rigorously benchmarking and evaluating large language models like GPT-4 and ChatGPT in synthesizing program code using Python under the Apache-2.0 license. ## 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 evalplus if… - Tags unique to evalplus: benchmark, chatgpt, efficiency, program-synthesis. - evalplus ships Docker support for self-hosted deployment. - When you need advanced benchmarks specific to large language model generated program synthesis, such as from GPT-4 or ChatGPT. ### 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 evalplus - Avoid if you require broad language model benchmarking that is not specifically focused on program synthesis capabilities. - Do not use evalplus if your project does not benefit from or need Docker-based isolation for code execution safety measures, such as in controlled lab environments without external dependencies. ## 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 evalplus and auto-evaluator? evalplus: Rigorous evaluation of LLM-synthesized code. 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 evalplus over auto-evaluator? Choose evalplus over auto-evaluator when Tags unique to evalplus: benchmark, chatgpt, efficiency, program-synthesis; evalplus ships Docker support for self-hosted deployment; When you need advanced benchmarks specific to large language model generated program synthesis, such as from GPT-4 or ChatGPT. ### When should I choose auto-evaluator over evalplus? Choose auto-evaluator over evalplus 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 evalplus? Avoid if you require broad language model benchmarking that is not specifically focused on program synthesis capabilities. Do not use evalplus if your project does not benefit from or need Docker-based isolation for code execution safety measures, such as in controlled lab environments without external dependencies. ### 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 evalplus or auto-evaluator more popular on GitHub? evalplus has more GitHub stars (1,794 vs 1,105). Stars measure visibility, not whether either tool fits your constraints. ### Are evalplus and auto-evaluator open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to evalplus or auto-evaluator? GraphCanon lists graph-backed alternatives at [evalplus alternatives](/tools/evalplus-evalplus/alternatives) and [auto-evaluator alternatives](/tools/rlancemartin-auto-evaluator/alternatives) ([evalplus markdown twin](/tools/evalplus-evalplus/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/evalplus-evalplus-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, evalplus or auto-evaluator? evalplus: 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 evalplus and auto-evaluator? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [evalplus trust report](/tools/evalplus-evalplus/trust); [auto-evaluator trust report](/tools/rlancemartin-auto-evaluator/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=evalplus-evalplus`](/api/graphcanon/graph?tool=evalplus-evalplus) - 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/_