onejune2018/Awesome-LLM-Eval
Awesome-LLM-Eval: a curated list of tools, datasets/benchmark, demos, leaderboard, papers, docs and models, mainly for Evaluation on LLMs. 一个由工具、基准/数据、演示、排行榜和大模型等组成的精选列表，主要面向基础大模型评测，旨在探求生成式AI的技术边界.
This project helps AI researchers, machine learning engineers, and data scientists understand and benchmark the performance of large language models (LLMs). It brings together a comprehensive list of tools, datasets, benchmarks, and leaderboards. Practitioners can use this to identify relevant resources for evaluating LLMs, whether for general capabilities, domain-specific tasks, or specific attributes like inference speed or factuality.
616 stars.
Use this if you need a centralized, up-to-date resource to find tools, datasets, and methodologies for evaluating large language models across various criteria and domains.
Not ideal if you are looking for an off-the-shelf software library to run evaluations directly, as this is primarily a curated list of external resources.
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616
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MIT
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Last pushed
Nov 24, 2025
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