Track, rank and evaluate open LLMs and chatbots
Evaluate code generation with diverse feedback types
Benchmark AI models by comparison
Browse and submit LLM evaluations
Retrain models for new data at edge devices
Push a ML model to Hugging Face Hub
Measure over-refusal in LLMs using OR-Bench
Explore GenAI model efficiency on ML.ENERGY leaderboard
Submit deepfake detection models for evaluation
Evaluate LLM over-refusal rates with OR-Bench
Benchmark models using PyTorch and OpenVINO
Evaluate open LLMs in the languages of LATAM and Spain.
Convert and upload model files for Stable Diffusion
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.