Search for model performance across languages and benchmarks
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Submit models for evaluation and view leaderboard
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View and submit language model evaluations
View and submit LLM evaluations
The Open Multilingual Llm Leaderboard is a platform designed to evaluate and compare the performance of multilingual language models across various languages and benchmarks. It serves as a central hub for researchers and developers to track progress, identify trends, and optimize models for diverse linguistic environments.
• Multi-Language Support: Evaluates model performance across dozens of languages, including low-resource and high-resource languages. • Benchmark Coverage: Incorporates widely recognized benchmarks such as Flores-101, Tatoeba, and others to ensure comprehensive evaluation. • Model Comparison: Allows users to compare performance metrics of different models side-by-side. • Interactive Interface: Provides a user-friendly dashboard for exploring results, filtering by language, and visualizing performance. • Regular Updates: Continuously updates with new models and benchmarks to reflect the latest advancements in multilingual AI.
What languages are supported on the Open Multilingual Llm Leaderboard?
The leaderboard supports dozens of languages, including English, Spanish, French, German, Chinese, Hindi, Arabic, and many others, with a focus on both high-resource and low-resource languages.
How often is the leaderboard updated?
The leaderboard is regularly updated to include new models, benchmarks, and languages as they become available.
Can I submit my own model for evaluation?
Yes, the platform allows researchers and developers to submit their models for evaluation, provided they meet the submission guidelines and requirements.