Explore GenAI model efficiency on ML.ENERGY leaderboard
Download a TriplaneGaussian model checkpoint
Compare code model performance on benchmarks
Predict customer churn based on input details
Search for model performance across languages and benchmarks
Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
Calculate memory usage for LLM models
Load AI models and prepare your space
Measure BERT model performance using WASM and WebGPU
Submit models for evaluation and view leaderboard
Browse and filter machine learning models by category and modality
Submit deepfake detection models for evaluation
Browse and submit model evaluations in LLM benchmarks
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.