OpenAI: GPT-4.1 Mini (batch)

GPT-4.1 Mini is a text model from OpenAI, offered here through the batch variant identified as openai/gpt-4.1-mini:batch. It sits in the middle of OpenAI's GPT-4.1 family: smaller than the flagship GPT-4.1, but built to deliver performance competitive with GPT-4o while running with substantially lower latency. The model was released by the provider on 14 April 2025, and its knowledge cutoff is 30 June 2024, so anything after that date is outside what it learned during training.

On the input side, GPT-4.1 Mini accepts text, images and files, which means you can send a prompt that mixes written instructions with a screenshot, a scanned page or an attached document. Output is text only. The context window is 1,047,576 tokens, just over a million, and the maximum output length is 32,768 tokens. That combination of a very large input window and a sizeable output budget makes it possible to work with long documents or extended conversations without splitting them into chunks.

Those capabilities point to a fairly specific set of uses. Long-context analysis is the obvious one: feeding in lengthy reports, contracts, codebases or support threads and asking for summaries, extractions or answers grounded in the whole document. Because images and files are accepted as input, document understanding tasks fit as well, such as pulling structured data out of PDFs or interpreting charts and diagrams alongside their surrounding text. Tool use and structured output support make it a reasonable choice for agent style workflows and for pipelines where the model must return data in a fixed shape rather than free prose.

Calling it through api14 works the same way as any other OpenAI-compatible endpoint. You send your request to the chat completions route and set the model field to "openai/gpt-4.1-mini:batch". The request body supports max_tokens, temperature, top_p, seed, response_format, structured_outputs, tools and tool_choice. In practice that means you can control sampling behaviour with temperature and top_p, make runs more reproducible with seed, constrain the reply with response_format or structured_outputs, and give the model callable functions through tools and tool_choice. Note that this is the batch variant, so it is aimed at workloads that tolerate asynchronous or queued processing rather than tight interactive loops.

If your application needs the strongest reasoning available in the family, or if you depend on very low latency for real time chat, a larger or non-batch model may be the better fit. The knowledge cutoff of 30 June 2024 also means questions about more recent events will need retrieval or fresh context supplied in the prompt. Within those bounds, GPT-4.1 Mini is a sensible default for high volume text and document tasks where the million token window matters more than top end reasoning depth.