hkust-nlp/ceval resource

Health v2 · maintenance only

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Adoption not part of the score

1867 stars · 84 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

C-Eval is a comprehensive Chinese evaluation benchmark for foundation models, consisting of 13,948 multiple-choice questions across 52 disciplines and four difficulty levels. The repository provides the dataset, evaluation scripts, and leaderboards for measuring LLM performance on Chinese-language tasks.

Use cases

• evaluate a large language model on Chinese-language knowledge
• benchmark my LLM against GPT-4 and ChatGPT on Chinese tasks
• find weaknesses of my model across 52 academic disciplines
• run standardized Chinese multiple-choice evaluations
• compare Chinese capabilities of open-source and proprietary models
• add a Chinese benchmark to my model evaluation pipeline

When to choose

• you need a standardized, widely-cited Chinese benchmark for foundation models
• you want multi-discipline coverage from middle school to professional exams
• you want results comparable to published leaderboards and lm-evaluation-harness

When to avoid

• you need evaluation in languages other than Chinese
• you need open-ended generation or reasoning benchmarks rather than multiple-choice
• you need a lightweight task-specific test rather than a broad academic suite

Facets

dataset · maturity stable

benchmarking testing data-generation large-language-models machine-learning education python chinese-benchmark evaluation-suite multiple-choice foundation-models neurips-2023 llm-evaluation natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="hkust-nlp/ceval")