--- title: "ACLUE vs ARES" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/isen-zhang-aclue-vs-stanford-futuredata-ares" tools: ["isen-zhang-aclue", "stanford-futuredata-ares"] --- # ACLUE vs ARES *GraphCanon updated Aug 6, 2026* ## Verdict Pick ACLUE if aCLUE is an evaluation benchmark for testing how well large language models understand ancient Chinese texts covering syntax, semantics, reasoning, and knowledge; pick ARES if automated evaluation for RAG systems with API integrations like OpenAI. [ACLUE](https://github.com/isen-zhang/ACLUE) reports 34 GitHub stars, 0 forks, and 0 open issues, last pushed Mar 20, 2024. [ARES](https://ares-ai.vercel.app/) has 731 stars, 67 forks, and 21 open issues, last pushed Mar 28, 2025. Figures are from public GitHub metadata via [ACLUE's repository](https://github.com/isen-zhang/ACLUE) and [ARES's repository](https://github.com/stanford-futuredata/ARES). | | [ACLUE](/tools/isen-zhang-aclue.md) | [ARES](/tools/stanford-futuredata-ares.md) | | --- | --- | --- | | Tagline | Evaluation Benchmark for Ancient Chinese Language Comprehension | Automated Evaluation of RAG Systems | | Stars | 34 | 731 | | Forks | 0 | 67 | | Open issues | 0 | 21 | | Language | Python | Python | | Adopt for | ACLUE is an evaluation benchmark for testing how well large language models understand ancient Chinese texts covering syntax, semantics, reasoning, and knowledge. | Automated evaluation for RAG systems with API integrations like OpenAI. | | Persona | - | - | | Runtime | - | - | | License | MIT License: Permissive open-source license allowing free use and modification of the software, including commercially. | Apache-2.0 | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ACLUE](/tools/isen-zhang-aclue.md) | [ARES](/tools/stanford-futuredata-ares.md) | | --- | --- | --- | | Days since push | 868d | 491d | | Open issues (now) | 0 | 21 | | Owner type | User | Organization | | Full report | [trust report](/tools/isen-zhang-aclue/trust.md) | [trust report](/tools/stanford-futuredata-ares/trust.md) | ## Decision facts: ACLUE - **Adopt for:** ACLUE is an evaluation benchmark for testing how well large language models understand ancient Chinese texts covering syntax, semantics, reasoning, and knowledge. - **License detail:** MIT License: Permissive open-source license allowing free use and modification of the software, including commercially. ## Decision facts: ARES - **Adopt for:** Automated evaluation for RAG systems with API integrations like OpenAI. ## Choose when ### Choose ACLUE if… - License: ACLUE is MIT, ARES is Apache-2.0. - Tags unique to ACLUE: ancient texts, chinese language, language models evaluation, nlp benchmarks. - When evaluating the performance of LLMs specifically on comprehending ancient Chinese language across 15 tasks ### Choose ARES if… - License: ARES is Apache-2.0, ACLUE is MIT. - Tags unique to ARES: automated scoring, human validation sets, python, rag evaluation. - Evaluating Retrieval-Augmented Generation (RAG) systems that require automatic scoring using human-annotated data and few-shot examples. ## When NOT to use ACLUE - For benchmarking modern Chinese or other languages not related to ancient Chinese comprehension - When the focus is strictly on contemporary texts without a need for historical language understanding capabilities ## When NOT to use ARES - Avoid if limited to non-GPU machines with less than ~100GB available disk space, as it encounters CUDA out-of-memory errors without compatible GPU setups. ## Common questions ### What is the difference between ACLUE and ARES? ACLUE: Evaluation Benchmark for Ancient Chinese Language Comprehension. ARES: Automated Evaluation of RAG Systems. See the comparison table for live GitHub stats and shared categories. ### When should I choose ACLUE over ARES? Choose ACLUE over ARES when License: ACLUE is MIT, ARES is Apache-2.0; Tags unique to ACLUE: ancient texts, chinese language, language models evaluation, nlp benchmarks; When evaluating the performance of LLMs specifically on comprehending ancient Chinese language across 15 tasks. ### When should I choose ARES over ACLUE? Choose ARES over ACLUE when License: ARES is Apache-2.0, ACLUE is MIT; Tags unique to ARES: automated scoring, human validation sets, python, rag evaluation; Evaluating Retrieval-Augmented Generation (RAG) systems that require automatic scoring using human-annotated data and few-shot examples. ### When should I avoid ACLUE? For benchmarking modern Chinese or other languages not related to ancient Chinese comprehension When the focus is strictly on contemporary texts without a need for historical language understanding capabilities ### When should I avoid ARES? Avoid if limited to non-GPU machines with less than ~100GB available disk space, as it encounters CUDA out-of-memory errors without compatible GPU setups. ### Is ACLUE or ARES more popular on GitHub? ARES has more GitHub stars (731 vs 34). Stars measure visibility, not whether either tool fits your constraints. ### Are ACLUE and ARES open source? Yes - both are open-source projects on GitHub (ACLUE: MIT, ARES: Apache-2.0). ### Where can I find alternatives to ACLUE or ARES? GraphCanon lists graph-backed alternatives at [ACLUE alternatives](/tools/isen-zhang-aclue/alternatives) and [ARES alternatives](/tools/stanford-futuredata-ares/alternatives) ([ACLUE markdown twin](/tools/isen-zhang-aclue/alternatives.md), [ARES markdown twin](/tools/stanford-futuredata-ares/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/isen-zhang-aclue-vs-stanford-futuredata-ares.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ACLUE or ARES? ACLUE: Dormant. ARES: 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 ACLUE and ARES? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ACLUE trust report](/tools/isen-zhang-aclue/trust); [ARES trust report](/tools/stanford-futuredata-ares/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=isen-zhang-aclue`](/api/graphcanon/graph?tool=isen-zhang-aclue) - 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/_