RaspizdAI/QUAD-Bench
QUAD-Bench: A Lightweight AI Reasoning & Acuity Benchmark QUAD-Bench is a compact, multiple-choice benchmark dataset designed for quick evaluation of Large Language Models (LLMs). The dataset contains 100 questions evenly distributed across 4 fundamental capabilities, requiring the model to select exactly one correct answer option (A, B, C, or D). 📊 Dataset Structure The benchmark consists of 100 questions divided into 4 categories (25 questions each):… See the full description on the dataset page: https://huggingface.co/datasets/RaspizdAI/QUAD-Bench.
QUAD-Bench: A Lightweight AI Reasoning & Acuity Benchmark
QUAD-Bench is a compact, multiple-choice benchmark dataset designed for quick evaluation of Large Language Models (LLMs). The dataset contains 100 questions evenly distributed across 4 fundamental capabilities, requiring the model to select exactly one correct answer option (A, B, C, or D).
📊 Dataset Structure
The benchmark consists of 100 questions divided into 4 categories (25 questions each):
📁 JSON Format
Each entry in dataset.json follows this simple schema:
{
"id": 1,
"category": "logic",
"question": "If all Bloops are Razzies and all Razzies are Lazzies, then all Bloops are definitely Lazzies.\nA) True\nB) False\nC) Cannot be determined\nD) None of the above",
"answer": "A"
}