Browse and submit LLM evaluations
View and compare language model evaluations
Display leaderboard for earthquake intent classification models
Measure execution times of BERT models using WebGPU and WASM
Calculate memory needed to train AI models
Request model evaluation on COCO val 2017 dataset
Search for model performance across languages and benchmarks
View RL Benchmark Reports
Quantize a model for faster inference
Explain GPU usage for model training
Teach, test, evaluate language models with MTEB Arena
Evaluate reward models for math reasoning
Explore and visualize diverse models
The Open Tw Llm Leaderboard is a platform designed for model benchmarking, specifically for Large Language Models (LLMs). It serves as a centralized hub where users can browse and submit evaluations of different LLMs. The tool provides a comparative analysis of various models, highlighting their strengths and weaknesses. This leaderboard is particularly useful for researchers, developers, and enthusiasts looking to understand the performance of different LLMs across various tasks and datasets.
What is the purpose of Open Tw Llm Leaderboard? The purpose is to provide a centralized platform for comparing and analyzing the performance of different Large Language Models.
How do I submit an evaluation to the leaderboard? Submissions can be made by following the guidelines provided on the platform, typically involving providing detailed metrics and results from your evaluation.
Do I need to register to use the leaderboard? No, browsing the leaderboard is generally accessible without registration. However, submitting an evaluation may require creating an account.