OpenAI: o1

OpenAI o1 is a text focused model from OpenAI, released on 17 December 2024. It belongs to the o1 family, which OpenAI describes as its latest and strongest model family. The defining idea behind the series is that the model spends more time thinking before it responds, and it was trained with large scale reinforcement learning to reason. If you have used earlier OpenAI chat models, the practical difference is that o1 is built to work through a problem internally rather than answer immediately.

On the input side, o1 accepts text, images and files, and it returns text. The context window is 200,000 tokens, with a maximum output of 100,000 tokens, so long documents and large prompts fit comfortably alongside a substantial generated response. Its knowledge cutoff is 31 October 2023, which matters when your task depends on events or library versions after that date. Supported request parameters include max_tokens, seed, response_format, structured_outputs, tools, tool_choice, reasoning and include_reasoning. The reasoning and include_reasoning parameters are specific to this family and let you control or surface the model's internal reasoning rather than treating it as a black box.

Those capabilities point to a fairly specific set of use cases. The large context and file input suit analysis of long documents, contracts, research papers or codebases where the answer depends on details spread across many pages. Image input extends this to diagrams, screenshots and scanned material that need interpretation alongside text. Because the model is trained to reason, it fits multi step problems: debugging, mathematical work, planning, and tasks where a wrong first guess is expensive. Tool and structured output support make it usable inside pipelines where the model must call functions or return JSON that downstream code can parse.

You call o1 through api14's OpenAI compatible API using the model id "openai/o1". Because the interface follows the OpenAI chat completions shape, existing OpenAI SDK clients generally work after you point the base URL at api14 and swap in that model id. The request parameters listed above are the ones to rely on: max_tokens, seed, response_format, structured_outputs, tools, tool_choice, reasoning and include_reasoning. If you need deterministic sampling for testing, seed is available; if you need machine readable output, structured_outputs and response_format cover that.

One limit worth noting is the knowledge cutoff of 31 October 2023, so anything requiring current information needs to come from your prompt, uploaded files or a tool call rather than the model's own knowledge. Output is text only, so image generation is out of scope. If your workload is simple, latency sensitive chat that does not benefit from extended reasoning, a lighter model may be a better fit.