Explore GenAI model efficiency on ML.ENERGY leaderboard
Compare and rank LLMs using benchmark scores
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Create demo spaces for models on Hugging Face
Find and download models from Hugging Face
Evaluate code generation with diverse feedback types
Analyze model errors with interactive pages
Submit deepfake detection models for evaluation
Convert Hugging Face models to OpenVINO format
Convert Hugging Face model repo to Safetensors
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Evaluate LLM over-refusal rates with OR-Bench
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.