Project Overview
The AI Model Benchmark & Evaluation Dashboard is a responsive, interactive web application designed to systematically compare, analyze, and display the performance metrics of leading open-source and proprietary large language models across diverse domains. By synthesizing rigorous test suite prompts, the platform provides clear, data-driven insights into model strengths, helping developers and researchers select the optimal model for specific enterprise and technical use cases.
Key Features & Capabilities
Interactive Evaluation Matrix: A structured, filterable, and sortable data table displaying granular performance scores (ranging from 1 to 5) across multiple benchmark categories, including Reasoning & Math, Factual Accuracy, Instruction Following, Coding & Algorithms, Indian Languages, and Responsible AI.
Dynamic Search & Filtering: Instant search capabilities allowing users to filter prompts by title, ID, or specific evaluation category to quickly isolate performance bottlenecks or highlights.
Category Insights & Best Performers: An executive summary dashboard highlighting class-leading models for specialized workloads—such as identifying Qwen_3.8_27B for regional Indian language tasks and gpt_oss_120b or Gemma_4_31B for heavy reasoning, coding, and mathematical logic.
Modern Responsive UI: Built with a clean, modern aesthetic utilizing component-based architecture and Tailwind CSS for seamless adaptability across mobile, tablet, and desktop viewports.
Performance Highlights (Summary of Findings)
Reasoning, Coding & Factual Accuracy: Models like gpt_oss_120b and Gemma_4_31B consistently achieve top-tier marks (scoring 5/5) in complex logic puzzles, algorithmic code generation, and factual retrieval.
Multilingual Capabilities: Qwen_3.8_27B demonstrates exceptional domain mastery across Indian regional languages (Hindi, Tamil, Bengali, Telugu, and Hinglish).
Safety & Alignment: Multiple models (gpt_oss_120b, Gemma_4_31B, and gpt_oss_20b) exhibit robust safety alignment, securing maximum scores in handling responsible AI and security boundary test cases.