Explore and compare LLM models through interactive leaderboards and submissions
Launch Argilla for data labeling and annotation
Monitor application health
Analyze data using Pandas Profiling
This project is a GUI for the gpustack/gguf-parser-go
Form for reporting the energy consumption of AI models.
Analyze your dataset with guided tools
Browse and filter LLM benchmark results
Try the Hugging Face API through the playground
Explore speech recognition model performance
M-RewardBench Leaderboard
Generate plots for GP and PFN posterior approximations
Display a Bokeh plot
The Open Japanese LLM Leaderboard is a comprehensive tool designed to explore and compare large language models (LLMs), with a specific focus on Japanese language support. It provides an interactive platform to evaluate and benchmark different LLMs, helping researchers, developers, and users understand their capabilities and performance.
What is the purpose of the Open Japanese LLM Leaderboard?
The leaderboard aims to provide a transparent and standardized way to compare and evaluate large language models, particularly those focused on Japanese language tasks.
How often is the leaderboard updated?
The leaderboard is regularly updated with new models and benchmark results to reflect the latest advancements in LLM development.
Can I submit a model that does not support Japanese?
While the leaderboard specializes in Japanese language models, submissions of non-Japanese models are accepted but may not be fully optimized for the platform's focus areas.