OpenCompass 2.0 Large Language Model Leaderboard

A real-time large language model leaderboard that provides comprehensive performance assessments.

CommonProductProductivityevaluationleaderboard

OpenCompass 2.0 is a platform dedicated to evaluating the performance of large language models. It utilizes multiple closed-source datasets for multi-dimensional assessments, providing models with an overall average score and specialized skill scores. The platform helps developers and researchers understand the performance of different models in areas like language, knowledge, reasoning, mathematics, and programming through its real-time updated leaderboard.

OpenCompass 2.0 Large Language Model Leaderboard

Multi-dimensional evaluation of model performance: language
knowledge
reasoning
mathematics
and programming.
Real-time leaderboard updates to showcase the latest model performance.
Detailed scoring for models across different datasets.
Support for viewing model configuration files to understand the technical details behind the scores.
Closed-source datasets ensure the fairness and authority of the assessments.
Easy navigation to GitHub for related configuration files.

This product is designed for researchers
developers
and enterprise decision-makers who need to evaluate and compare the performance of different large language models to select the best one for their projects.

Researchers use OpenCompass 2.0 to evaluate different models' performance on specific tasks.
Developers leverage the leaderboard to select suitable language models for developing chatbots.
Enterprise decision-makers use the leaderboard data to determine which model to adopt for optimizing their products.

Visit the official website of OpenCompass 2.0.
View the real-time updated leaderboard of large language models.
Select a model of interest and view its scores across different dimensions.
Click on the score to navigate to GitHub and view the model's configuration file.
Based on the configuration file and technical details

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70237

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2.7

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