--- title: "auto-evaluator vs Open-LLM-Leaderboard" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/rlancemartin-auto-evaluator-vs-vila-lab-open-llm-leaderboard" tools: ["rlancemartin-auto-evaluator", "vila-lab-open-llm-leaderboard"] --- # auto-evaluator vs Open-LLM-Leaderboard *GraphCanon updated Sep 20, 2026* ## Verdict 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; pick Open-LLM-Leaderboard if open-LLM-Leaderboard evaluates large language models on open-style questions using a GPT-4-based evaluator and aggregates results in an accessible leaderboard format. [auto-evaluator](https://autoevaluator.langchain.com/) reports 1.1k GitHub stars, 92 forks, and 3 open issues, last pushed May 10, 2023. [Open-LLM-Leaderboard](https://huggingface.co/spaces/Open-Style/OSQ-Leaderboard) has 53 stars, 7 forks, and 1 open issues, last pushed Jun 27, 2024. Figures are from public GitHub metadata via [auto-evaluator's repository](https://github.com/rlancemartin/auto-evaluator) and [Open-LLM-Leaderboard's repository](https://github.com/VILA-Lab/Open-LLM-Leaderboard). | | [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) | [Open-LLM-Leaderboard](/tools/vila-lab-open-llm-leaderboard.md) | | --- | --- | --- | | Tagline | A lightweight evaluation tool for question-answering using Langchain | Tracks LLM performance on open-style questions | | Stars | 1,102 | 53 | | Forks | 92 | 7 | | Open issues | 3 | 1 | | Language | Python | Python | | 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. | Open-LLM-Leaderboard evaluates large language models on open-style questions using a GPT-4-based evaluator and aggregates results in an accessible leaderboard format. | | Persona | - | - | | Runtime | - | - | | License | - | CC-BY-4.0 | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) | [Open-LLM-Leaderboard](/tools/vila-lab-open-llm-leaderboard.md) | | --- | --- | --- | | Days since push | 1216d | 804d | | Open issues (now) | 3 | 1 | | Stars delta | -3 (30d) | 0 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/rlancemartin-auto-evaluator/trust.md) | [trust report](/tools/vila-lab-open-llm-leaderboard/trust.md) | ## Shared compatibility - **Python**: [auto-evaluator](/tools/rlancemartin-auto-evaluator.md) - Python runtime; [Open-LLM-Leaderboard](/tools/vila-lab-open-llm-leaderboard.md) - Python runtime ## 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. ## Decision facts: Open-LLM-Leaderboard - **Adopt for:** Open-LLM-Leaderboard evaluates large language models on open-style questions using a GPT-4-based evaluator and aggregates results in an accessible leaderboard format. ## Choose when ### 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. - More GitHub stars (1.1k vs 53) - visibility, not fit. ### Choose Open-LLM-Leaderboard if… - Tags unique to Open-LLM-Leaderboard: leaderboard, llm-evaluation, model-performance-tracking, open-style-questions. - You need to evaluate your LLM's performance on open-ended, human-like question formats across multiple datasets without setting up the evaluation process yourself. - More recently updated (last pushed Jun 27, 2024). ## 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. ## When NOT to use Open-LLM-Leaderboard - You are seeking evaluations solely based on closed-response or multiple-choice questions where specific answers can be easily verified by non-LLM means. - Your project has constraints against using commercial LLMs like GPT-4 for evaluation due to cost, licensing issues, or the need for open-source alternatives. ## Common questions ### What is the difference between auto-evaluator and Open-LLM-Leaderboard? auto-evaluator: A lightweight evaluation tool for question-answering using Langchain. Open-LLM-Leaderboard: Tracks LLM performance on open-style questions. See the comparison table for live GitHub stats and shared categories. ### When should I choose auto-evaluator over Open-LLM-Leaderboard? Choose auto-evaluator over Open-LLM-Leaderboard 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; More GitHub stars (1.1k vs 53) - visibility, not fit. ### When should I choose Open-LLM-Leaderboard over auto-evaluator? Choose Open-LLM-Leaderboard over auto-evaluator when Tags unique to Open-LLM-Leaderboard: leaderboard, llm-evaluation, model-performance-tracking, open-style-questions; You need to evaluate your LLM's performance on open-ended, human-like question formats across multiple datasets without setting up the evaluation process yourself; More recently updated (last pushed Jun 27, 2024). ### 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. ### When should I avoid Open-LLM-Leaderboard? You are seeking evaluations solely based on closed-response or multiple-choice questions where specific answers can be easily verified by non-LLM means. Your project has constraints against using commercial LLMs like GPT-4 for evaluation due to cost, licensing issues, or the need for open-source alternatives. ### Is auto-evaluator or Open-LLM-Leaderboard more popular on GitHub? auto-evaluator has more GitHub stars (1,102 vs 53). Stars measure visibility, not whether either tool fits your constraints. ### Are auto-evaluator and Open-LLM-Leaderboard open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to auto-evaluator or Open-LLM-Leaderboard? GraphCanon lists graph-backed alternatives at [auto-evaluator alternatives](/tools/rlancemartin-auto-evaluator/alternatives) and [Open-LLM-Leaderboard alternatives](/tools/vila-lab-open-llm-leaderboard/alternatives) ([auto-evaluator markdown twin](/tools/rlancemartin-auto-evaluator/alternatives.md), [Open-LLM-Leaderboard markdown twin](/tools/vila-lab-open-llm-leaderboard/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/rlancemartin-auto-evaluator-vs-vila-lab-open-llm-leaderboard.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, auto-evaluator or Open-LLM-Leaderboard? auto-evaluator: Dormant. Open-LLM-Leaderboard: 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 auto-evaluator and Open-LLM-Leaderboard? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [auto-evaluator trust report](/tools/rlancemartin-auto-evaluator/trust); [Open-LLM-Leaderboard trust report](/tools/vila-lab-open-llm-leaderboard/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=rlancemartin-auto-evaluator`](/api/graphcanon/graph?tool=rlancemartin-auto-evaluator) - 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/_