Text-embedding-3 series models are the latest and most capable embedding model from OpenAI.

Text-embedding-3 series models are the latest and most capable embedding model from OpenAI.

Smaller, faster, and 80% cheaper than o1-preview, performs well at code generation and small context operations.

o3-mini includes the o1 features with significant cost-efficiencies for scenarios requiring high performance.

Focused on advanced reasoning and solving complex problems, including math and science tasks. Ideal for applications that require deep contextual understanding and agentic workflows.

gpt-4.1-nano provides gains in coding, instruction following, and long-context handling along with lower latency and cost

gpt-4.1 outperforms gpt-4o across the board, with major gains in coding, instruction following, and long-context understanding

OpenAI's most advanced multimodal model in the gpt-4o family. Can handle both text and image inputs.

gpt-5-mini is a lightweight version for cost-sensitive applications.

gpt-5 is designed for logic-heavy and multi-step tasks.

gpt-5-chat (preview) is an advanced, natural, multimodal, and context-aware conversations for enterprise applications.

An affordable, efficient AI solution for diverse text and image tasks.

gpt-5-nano is optimized for speed, ideal for applications requiring low latency.

Focused on advanced reasoning and solving complex problems, including math and science tasks. Ideal for applications that require deep contextual understanding and agentic workflows.

gpt-4.1-mini outperform gpt-4o-mini across the board, with major gains in coding, instruction following, and long-context handling

o3 includes significant improvements on quality and safety while supporting the existing features of o1 and delivering comparable or better performance.

A 398B parameters (94B active) multilingual model, offering a 256K long context window, function calling, structured output, and grounded generation.

o4-mini includes significant improvements on quality and safety while supporting the existing features of o3-mini and delivering comparable or better performance.

Command A is a highly efficient generative model that excels at agentic and multilingual use cases.

Command R is a scalable generative model targeting RAG and Tool Use to enable production-scale AI for enterprise.