arXiv:2605.19276v3 Announce Type: replace-cross 
Abstract: In recent years, the field of artificial intelligence has undergone a paradigm shift from task-specific small-scale models to general-purpose large language models (LLMs). With the rapid iteration of LLMs, objective, quantitative, and comprehensive evaluation of their capabilities has become a critical link in advancing technological development. Currently, the mainstream static benchmark dataset-based evaluation methods face challenges such as the diversity of task types, inconsistent evaluation criteria, and fragmentation of data and processing workflows, making it difficult to efficiently conduct cross-domain and large-scale model evaluation. To address the aforementioned issues, this paper proposes and open-sources OpenCompass, a one-stop, scalable, and high-concurrency-supported general-purpose LLM evaluation platform. Adhering to the design philosophy of modularization and component decoupling, the platform boasts three core advantages: high compatibility, flexibility, and high concurrency. The core architecture of OpenCompass comprises five key components: the Configuration System, Task Partitioning Module, Execution and Scheduling Module, Task Execution Unit, and Result Visualization Module. Its workflow provides rule-based, LLM-as-a-Judge, and cascaded evaluators to adapt to the requirements of different task scenarios. Supporting mainstream benchmark datasets across multiple domains, including knowledge, reasoning, computation, science, language, code, etc., the platform offers a unified and efficient LLM evaluation tool for both academia and industry, facilitating the accurate identification of strengths and weaknesses of LLMs as well as their subsequent optimization.

تم تقديم OpenCompass كمنصة تقييم قابلة للتوسع لنماذج اللغة الكبيرة (LLMs)، حيث تتناول التحديات التي تواجه طرق التقييم الحالية التي تعتمد على مجموعات بيانات مرجعية ثابتة. تهدف هذه المنصة إلى توفير حل شامل وفعال لتقييم قدرات LLM عبر مهام ومجالات متنوعة.

OpenCompass se ha presentado como una plataforma de evaluación escalable para modelos de lenguaje grandes (LLMs), abordando los desafíos de los métodos de evaluación actuales que dependen de conjuntos de datos de referencia estáticos. Esta plataforma tiene como objetivo proporcionar una solución integral y eficiente para evaluar las capacidades de los LLM en diversas tareas y dominios.

OpenCompass a été introduit comme une plateforme d'évaluation évolutive pour les grands modèles de langage (LLMs), répondant aux défis des méthodes d'évaluation actuelles qui reposent sur des ensembles de données de référence statiques. Cette plateforme vise à fournir une solution complète et efficace pour évaluer les capacités des LLM à travers des tâches et des domaines divers.

OpenCompass has been introduced as a scalable evaluation platform for large language models (LLMs), addressing the challenges of current evaluation methods that rely on static benchmark datasets. This platform aims to provide a comprehensive and efficient solution for assessing LLM capabilities across diverse tasks and domains.