Track, rank and evaluate open LLMs and chatbots
Compare code model performance on benchmarks
View LLM Performance Leaderboard
Calculate GPU requirements for running LLMs
Search for model performance across languages and benchmarks
Convert PyTorch models to waifu2x-ios format
Calculate memory needed to train AI models
Explore and visualize diverse models
Benchmark AI models by comparison
Evaluate LLM over-refusal rates with OR-Bench
GIFT-Eval: A Benchmark for General Time Series Forecasting
Convert Hugging Face model repo to Safetensors
View and submit LLM benchmark evaluations
The Open LLM Leaderboard is a comprehensive tool designed to track, rank, and evaluate open-source Large Language Models (LLMs) and chatbots. It provides a transparent and standardized platform to compare models based on various benchmarks and metrics, helping developers, researchers, and users make informed decisions. By focusing on performance, efficiency, and capabilities, the Leaderboard serves as a go-to resource for understanding the evolution and advancements in the field of LLMs.
What metrics are used to rank LLMs? The Leaderboard uses a variety of metrics, including performance benchmarks, speed, memory usage, and specific task accuracy to ensure a holistic evaluation of each model.
Can I compare custom or non-listed models? Yes, the platform allows users to input custom models for comparison, providing flexibility for researchers and developers working on niche or proprietary LLMs.
How often is the Leaderboard updated? The Leaderboard is updated regularly to reflect new releases and improvements in existing models, ensuring users always have access to the latest information.