Rank machines based on LLaMA 7B v2 benchmark results
Evaluate adversarial robustness using generative models
Launch web-based model application
View NSQL Scores for Models
Browse and evaluate ML tasks in MLIP Arena
View RL Benchmark Reports
Explore and submit models using the LLM Leaderboard
View and submit LLM benchmark evaluations
Upload a machine learning model to Hugging Face Hub
Compare LLM performance across benchmarks
Evaluate and submit AI model results for Frugal AI Challenge
Open Persian LLM Leaderboard
Request model evaluation on COCO val 2017 dataset
Llm Bench is a platform designed for model benchmarking, specifically tailored to evaluate and rank machines based on LLaMA 7B v2 benchmark results. It provides a comprehensive way to compare performance across different hardware setups, helping users identify the most efficient configurations for their needs.
What is Llm Bench used for?
Llm Bench is used to evaluate and compare the performance of different machines based on LLaMA 7B v2 benchmark results, helping users optimize their hardware configurations.
Which models does Llm Bench support?
Llm Bench is specifically designed to support the LLaMA 7B v2 model for benchmarking.
How do I interpret the benchmark results?
Benchmark results are displayed in a global leaderboard, showing your machine's performance metrics such as speed and accuracy compared to others. Higher rankings indicate better performance.