OpenAI: GPT-4.1

GPT-4.1 is a flagship large language model from OpenAI, released by the provider on 14 April 2025. It sits in the text category and is positioned for advanced instruction following, real-world software engineering, and long-context reasoning. If you are already working within the OpenAI family of models, this is the successor tier to GPT-4o, and it is aimed at workloads where careful adherence to instructions and large amounts of context matter more than raw speed.

The model accepts text, images, and files as input, and it returns text. Its context window is 1,047,576 tokens, which is just over one million tokens, and the maximum output is 32,768 tokens. The knowledge cutoff is 30 June 2024, so anything after that date is outside what the model was trained on. The combination of a very large context window and a moderate output ceiling means the model is well suited to reading far more than it writes, which is typical of analysis, review, and retrieval-style tasks.

Those capabilities point to a few practical uses. Long-context reasoning makes it a fit for working over large codebases, lengthy specifications, or multi-document sets in a single request rather than chunking them. Real-world software engineering suggests code review, refactoring, debugging, and test generation. Advanced instruction following helps with structured extraction and transformation tasks where the output format must be respected. Because images and files are accepted as input, you can also mix screenshots, diagrams, or documents into the same request as text.

You call the model through api14's OpenAI-compatible API using the model id "openai/gpt-4.1". The supported request parameters are max_completion_tokens, max_tokens, response_format, seed, structured_outputs, temperature, tool_choice, tools, and top_p. In practice that means you can control output length, request deterministic sampling with a seed, set temperature and top_p for randomness, constrain the response shape with response_format or structured_outputs, and define function calling through tools and tool_choice.

One limit worth noting is the output ceiling of 32,768 tokens. If your task is to generate a very long document in one pass, that cap will bind before the input context does, and you may need to split generation across calls. The knowledge cutoff of 30 June 2024 also means the model has no built-in awareness of later events, so anything recent has to come from the prompt or from tools you provide.