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GPT-4.1 is a model for complex tasks. It is well suited for problem solving across domains.

GPT-4.1 mini provides a balance between intelligence, speed, and cost that makes it an attractive model for many use cases.

GPT-4.1-nano is the smallest and most affordable model in the GPT-4.1 family. It's designed for tasks that require basic capabilities at the lowest possible cost.

GGPT-4o (“o” for “omni”) is a versatile, high-intelligence flagship model. It accepts both text and image inputs, and produces text outputs (including Structured Outputs). It is the best model for most tasks, and is currently the most capable model outside of the o-series models.

GPT-4o mini is a smaller, more affordable version of GPT-4o that maintains high quality while being more cost-effective. It's designed for tasks that don't require the full capabilities of GPT-4o.

GPT-5 is a flagship model for coding, reasoning, and agentic tasks across domains.

GPT-5.1 is a flagship model for coding and agentic tasks with configurable reasoning and non-reasoning effort.

GPT-5.1-Codex is a version of GPT-5 optimized for agentic coding tasks in Codex or similar environments. It's available in the Responses API only, and the underlying model snapshot will be regularly updated.

GPT-5.1-Codex-Max GPT‑5.1-Codex-Max is purpose-built for agentic coding. It's only available in the Responses API.

GPT-5.2 is OpenAI's flagship model for coding and agentic tasks across industries. Supports both reasoning and chat completions endpoints.

GPT-5.2-Codex is an upgraded version of GPT-5.2 optimized for agentic coding tasks in Codex or similar environments. GPT-5.2-Codex supports low, medium, high, and xhigh reasoning effort settings.

GPT-5.2 pro is available in the Responses API only to enable support for multi-turn model interactions before responding to API requests, and other advanced API features in the future. Supports reasoning.effort: medium, high, xhigh.

GPT-5.3-Codex is optimized for agentic coding tasks in Codex or similar environments. GPT-5.3-Codex supports low, medium, high, and xhigh reasoning effort settings.

GPT-5.4 is OpenAI's frontier model for complex professional work. Reasoning.effort supports: none (default), low, medium, high and xhigh.

GPT-5.4 mini brings the strengths of GPT-5.4 to a faster, more efficient model designed for high-volume workloads.

GPT-5.4 nano is designed for tasks where speed and cost matter most like classification, data extraction, ranking, and sub-agents.

GPT-5.4 pro uses more compute to think harder and provide consistently better answers. GPT-5.4 pro is available in the Responses API only to enable support for multi-turn model interactions before responding to API requests, and other advanced API features in the future. Since GPT-5.4 pro is designed to tackle tough problems, some requests may take several minutes to finish. To avoid timeouts, try using background mode. GPT-5.4 pro supports reasoning.effort: medium, high, xhigh.

GPT-5-Codex is a version of GPT-5 optimized for agentic coding tasks in agents. It's available in the Responses API only, and the underlying model snapshot will be regularly updated.

GPT-5 mini is a faster, cost-efficient version of GPT-5 for well-defined tasks.

GPT-5 nano is the fastest, most cost-efficient version of GPT-5. Great for summarization and classification tasks.

GPT-5 pro uses more compute to think harder and provide consistently better answers. GPT-5 pro is available in the Responses API only to enable support for multi-turn model interactions before responding to API requests, and other advanced API features in the future. As the most advanced reasoning model, GPT-5 pro defaults to (and only supports) reasoning.effort: high. GPT-5 pro does not support code interpreter.

The o1 series of models are trained with reinforcement learning to perform complex reasoning. o1 models think before they answer, producing a long internal chain of thought before responding to the user.

o3 is a well-rounded and powerful model across domains. It is capable of math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following. Use it to think through multi-step problems that involve analysis across text, code, and images.

o3-mini is a smaller, more affordable version of o3. It's a small reasoning model, providing high intelligence at the same cost and latency targets of o1-mini. o3-mini supports key developer features, like Structured Outputs, function calling, and Batch API.

o4-mini is a smaller, more affordable version of o4 that maintains high quality while being more cost-effective. It's optimized for fast, effective reasoning with exceptionally efficient performance in coding and visual tasks.