Open ASR Leaderboard is a web app that displays interactive leaderboards for automatic speech recognition models. Below are 7 llm eval & observability apps with similar functionality to Open ASR Leaderboard, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
Open Universal Arabic ASR Leaderboard provides a sortable and interactive table to compare the performance of various Arabic speech recognition models. Users can view word and character error rates across multiple test sets, making it easier for researchers and developers to benchmark and select models for their needs.
Open LLM Leaderboard is a web application that allows users to compare, filter, and evaluate open-source language models based on various benchmarks. It provides interactive tools for AI researchers and practitioners to assess model performance and make informed choices.
Open PL LLM Leaderboard is a web-based tool that allows users to compare large language models based on their performance on various benchmarks. It provides interactive filtering and detailed scores for AI researchers and practitioners.
La Leaderboard is a web application that allows users to browse, filter, and analyze the results and performance metrics of large language models. It includes features for comparing models, viewing runtime and CO₂ impact, and entering custom results, serving AI researchers and practitioners.
Open LLM Leaderboard is a web application that displays and analyzes benchmark data for large language models. Users can view, filter, and compare model performance metrics over time, supporting AI researchers and practitioners in evaluating LLMs.
Open Persian LLM Leaderboard is a web application that allows users to view, compare, and filter Persian language models by various metrics. It is designed for AI researchers and developers interested in benchmarking and evaluating LLMs for Persian.
Open Chinese LLM Leaderboard is a web app for browsing, filtering, and analyzing benchmarks of Chinese large language models. It provides interactive charts and performance trends, helping AI researchers and practitioners compare models efficiently.
