Explore GenAI model efficiency on ML.ENERGY leaderboard
Upload ML model to Hugging Face Hub
Calculate memory usage for LLM models
Create and upload a Hugging Face model card
Display and submit LLM benchmarks
Display model benchmark results
Convert Stable Diffusion checkpoint to Diffusers and open a PR
Rank machines based on LLaMA 7B v2 benchmark results
Compare code model performance on benchmarks
Load AI models and prepare your space
View NSQL Scores for Models
Upload a machine learning model to Hugging Face Hub
Explore and benchmark visual document retrieval models
The ML.ENERGY Leaderboard is a platform designed to benchmark and compare the energy consumption and performance of various AI models. It provides a transparent and standardized way to evaluate the efficiency of different models, enabling users to make informed decisions about their implementations. The leaderboard focuses specifically on GenAI energy efficiency, helping developers and organizations identify models that balance performance with energy usage.
What is the ML.ENERGY Leaderboard?
The ML.ENERGY Leaderboard is a tool for benchmarking AI models based on their energy consumption and performance, helping users find efficient solutions.
How are models evaluated on the leaderboard?
Models are evaluated based on their energy consumption during inference and training, as well as their performance metrics such as accuracy and speed.
How often is the leaderboard updated?
The leaderboard is continuously updated with new models and data to reflect the latest advancements in AI research and development.