AI Models

LeNet-5 is a pioneering convolutional neural network developed by Yann LeCun and colleagues in 1998. It was designed for handwritten digit recognition and is considered one of the foundational architectures in deep learning, establishing many patterns still used in modern CNNs.

The latest iteration of GPT-5 with improved instruction following, reduced hallucinations, and enhanced safety. Offers the best balance of capability and reliability for production use.

OpenAI's most advanced language model to date. Features unprecedented reasoning, creativity, and multimodal understanding. Represents a major leap in AI capabilities across all domains.

The enhanced version of o1 with more compute for complex reasoning. Best for the most challenging problems requiring deep analysis.

A smaller, faster reasoning model optimized for coding and STEM tasks. Offers strong logical capabilities at a lower cost than o1.

A fast and cost-effective model suitable for many everyday tasks. Good balance of capability and affordability for simpler use cases.

OpenAI's original GPT-4 model. A highly capable large language model for complex tasks requiring advanced reasoning and broad knowledge.

An optimized version of GPT-4 with vision capabilities and improved performance. Supports both text and image inputs with a 128K context window.

A cost-effective reasoning model that balances strong logical capabilities with faster response times. Great for everyday reasoning tasks.

OpenAI's most powerful reasoning model. Uses extended thinking time to solve complex problems in math, science, and coding. Achieves expert-level performance on technical benchmarks.

The most efficient GPT-4.1 variant, optimized for high-volume, low-latency applications. Best for simple tasks and real-time applications.

A smaller, faster, and more affordable version of GPT-4.1. Ideal for tasks requiring quick responses while maintaining strong performance.