README.md

metadata

title: Official Benchmarks Leaderboard 2026
emoji: 🏆
colorFrom: purple
colorTo: blue
sdk: gradio
sdk_version: 5.50.0
app_file: app.py
pinned: false

🏆 Official Benchmarks Leaderboard 2026

A unified leaderboard for 11 official HuggingFace benchmarks. Compare AI models across math, coding, knowledge, vision, agent, and language tasks.

✨ Features

• 📊 11 Official Benchmarks: GSM8K, MMLU-Pro, GPQA, HLE, SWE-bench, AIME, HMMT, and more
• 🎛️ Quick Filters: One-click presets for model sizes and benchmark categories
• 🔍 Interactive Search: Filter by model name or provider
• 📏 Size Range Slider: Filter models by parameter count (0-1100B+)
• 🎯 Category Selection: Choose specific benchmark categories to display
• 📥 Export CSV: Download filtered leaderboard data
• 🔄 Sortable Columns: Click any header to sort the table
• 🎨 Modern Design: Clean, responsive interface with provider logos

🎯 Benchmarks Included

📐 Math

• GSM8K: Grade School Math (8.5K problems)
• AIME 2026: American Invitational Mathematics Examination
• HMMT 2026: Harvard-MIT Mathematics Tournament

🧠 Knowledge

• MMLU-Pro: Massive Multi-task Language Understanding
• GPQA Diamond: PhD-level expert questions
• HLE: Humanity's Last Exam

💻 Coding

• SWE-bench Verified: Real-world software engineering tasks
• SWE-bench Pro: Advanced software engineering challenges

👁️ Vision

• olmOCR: OCR evaluation benchmark

🤖 Agent

• Terminal-Bench 2.0: Terminal command understanding

💬 Language

• EvasionBench: Language understanding challenges

🚀 Quick Start

The leaderboard loads automatically from the HuggingFace dataset: OpenEvals/leaderboard-data

Quick Filters:

• 🔹 Small (<10B), 🔸 Medium (10-100B), 🔶 Large (100B+) - Filter by model size
• 💻 Coding, 🧠 Knowledge, 📐 Math, etc. - Show only specific categories

📊 Data Source

Dataset: OpenEvals/leaderboard-data

All scores are aggregated from official HuggingFace benchmark leaderboards. The dataset is updated regularly with the latest model evaluations.

💻 Local Development

# Install dependencies
pip install -r requirements.txt

# Run the app
python app.py

📁 Project Structure

.
├── app.py                    # Main Gradio application
├── utils/
│   ├── data_loader.py       # Load data from HuggingFace dataset
│   ├── filters.py           # Filter and search logic
│   ├── formatters.py        # Data formatting utilities
│   └── html_generator.py    # Generate HTML leaderboard table
├── static/
│   └── sortTable.js         # Client-side table sorting
├── data/
│   └── provider_logos.json  # Provider avatar URLs
└── requirements.txt         # Python dependencies

🔧 Technologies

• Gradio 5.50.0: Interactive web interface
• Datasets: HuggingFace datasets library
• Pandas: Data manipulation
• RangeSlider: Custom Gradio component for size filtering

📝 License

Data is sourced from official HuggingFace benchmarks. Please refer to individual benchmark pages for specific licensing information.

---

Made with ❤️ by the Benchmarks Team