FlagEvalTranslation site

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FlagEval (Libra) is a large model evaluation platform developed by BAAI in collaboration with multiple university teams. It employs a 'Capability-Task-Metric' three-dimen...

Location:
China
Language:
CN
Collection time:
2025-05-30
FlagEvalFlagEval

In today’s rapidly evolving AI landscape, evaluating large models is crucial for assessing their performance and potential. The Beijing Academy of Artificial Intelligence (BAAI), in collaboration with multiple university teams, has launched FlagEval (Libra), a large model evaluation platform designed to provide researchers and developers with scientific, fair, and open evaluation benchmarks and toolsets.

Website Introduction

FlagEval caters to AI researchers and developers, offering comprehensive large model evaluation services to help users gain deep insights into their models’ strengths and weaknesses.

Key Features

The platform employs a ‘Capability-Task-Metric‘ three-dimensional evaluation framework, encompassing over 30 capabilities, 5 tasks, and 4 major categories of metrics, totaling more than 600 evaluation dimensions. The task dimension includes 22 subjective and objective evaluation datasets and 84,433 questions.

Related Projects

FlagEval is a vital component of BAAI’s FlagOpen large model open-source technology system, aiming to build a comprehensive open-source algorithm system and an all-in-one foundational software platform to support large model technology development.

Advantages

The platform supports multiple chip architectures (such as NVIDIA, Ascend, Cambricon, Kunlun) and deep learning frameworks (like PyTorch, MindSpore). It also offers automated and adaptive evaluation mechanisms, significantly enhancing evaluation efficiency and objectivity.

Pricing

Currently, FlagEval is open to users. For specific pricing details, please refer to the latest information on the official website.

Summary

Founded in 2018 and based in Beijing, China, BAAI is dedicated to advancing artificial intelligence technology. Through the FlagEval platform, users can comprehensively assess large model performance, identify potential issues, and optimize models to enhance the quality and efficiency of AI applications.

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