Browse and submit language model benchmarks
Calculate GPU requirements for running LLMs
Track, rank and evaluate open LLMs and chatbots
Browse and filter ML model leaderboard data
View and submit LLM evaluations
Explore and visualize diverse models
Launch web-based model application
Teach, test, evaluate language models with MTEB Arena
Display genomic embedding leaderboard
Download a TriplaneGaussian model checkpoint
Compare LLM performance across benchmarks
Open Persian LLM Leaderboard
Browse and filter machine learning models by category and modality
The HHEM Leaderboard is a platform designed for model benchmarking, allowing users to browse and submit language model benchmarks. It serves as a centralized hub for comparing the performance of various language models across different tasks and datasets. The leaderboard provides a transparent and standardized way to track advancements in language model capabilities.
What does HHEM stand for?
HHEM stands for Human-Human Empirical Metrics, focusing on evaluating language models based on human-like performance benchmarks.
Can I submit my own language model benchmarks?
Yes, HHEM Leaderboard allows users to submit benchmarks for their own language models, provided they follow the submission guidelines and criteria.
How often are the benchmarks updated?
The benchmarks are updated regularly as new models are submitted or as existing models are re-evaluated with updated metrics.