Explore GenAI model efficiency on ML.ENERGY leaderboard
Convert PyTorch models to waifu2x-ios format
Evaluate adversarial robustness using generative models
Compare audio representation models using benchmark results
Browse and submit model evaluations in LLM benchmarks
Merge machine learning models using a YAML configuration file
Evaluate and submit AI model results for Frugal AI Challenge
Evaluate reward models for math reasoning
Measure BERT model performance using WASM and WebGPU
Convert Stable Diffusion checkpoint to Diffusers and open a PR
Evaluate LLM over-refusal rates with OR-Bench
View and compare language model evaluations
Display genomic embedding leaderboard
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.