---
license: mit
task_categories:
- tabular-classification
language:
- en
tags:
- artificial-intelligence
- machine-learning
- model-benchmark
- deep-learning
size_categories:
- n<1K
---

# AI Model Performance Benchmark Dataset

## Description
This dataset contains structured benchmark data of artificial intelligence models across multiple domains including computer vision, natural language processing, audio classification, multimodal systems, and edge AI.

It provides model specifications such as parameter size, training dataset scale, accuracy, F1 score, inference latency, memory usage, and estimated power consumption.

## Columns
- model_name: Name of the AI model
- model_type: Category of AI system
- parameters_million: Number of model parameters (in millions)
- training_dataset_size_million: Training dataset size (in millions of samples)
- accuracy_percent: Model accuracy percentage
- f1_score: F1 performance score
- inference_latency_ms: Inference speed in milliseconds
- memory_usage_mb: Runtime memory usage in MB
- power_consumption_watt: Estimated power consumption

## Purpose
This dataset is designed for:
- AI performance benchmarking
- Machine learning research simulation
- Educational purposes
- Model efficiency comparison studies

## Format
CSV structured dataset