OpenAI: GPT-5

GPT-5 is a text model from OpenAI, listed on api14 under the model id openai/gpt-5. It sits in the text category and is described by the provider as OpenAI's most advanced model, with improvements in reasoning, code quality and user experience. It was released by the provider on 7 August 2025, and its knowledge cutoff is 30 September 2024.

The model accepts text, images and files as input, and it produces text as output. Its context window is 400,000 tokens, which is large enough to hold long documents, extended conversations or sizeable codebases in a single request. The maximum output is 128,000 tokens, so responses can be long when the task calls for it. Because image and file inputs are supported alongside text, you can send mixed material such as a screenshot plus a written question, or a document plus instructions, and receive a text answer.

Those capabilities point to a few practical uses. Step-by-step reasoning and instruction following suit analytical work: working through multi-stage problems, reviewing a plan for gaps, or extracting structured answers from long reports. Code quality matters for generation, refactoring and explanation tasks, especially when the relevant files are passed in directly. The combination of a large context window and file input fits document-heavy workflows such as summarising contracts, comparing versions of a specification, or answering questions against a corpus you supply in the request. Image input extends this to material that arrives as screenshots, diagrams or scanned pages.

You call it through api14's OpenAI-compatible API using the model id openai/gpt-5, so existing OpenAI SDKs and clients work with only the base URL and key changed. The request parameters it supports are include_reasoning, max_completion_tokens, max_tokens, reasoning, reasoning_effort, response_format, seed, structured_outputs, tool_choice, tools and verbosity. In practice that means you can cap output length, ask for reasoning to be surfaced or hidden, tune how much reasoning effort is spent, request JSON or schema-constrained output via response_format and structured_outputs, set a seed for reproducibility, and define tools with tool_choice for function calling. Verbosity gives another lever over how expansive the answer is.

Two constraints are worth noting when you choose a model. Output is text only, so if you need generated images or audio, this is not the model for that. The knowledge cutoff of 30 September 2024 also means anything after that date has to come from the prompt, from files you attach, or from tools you provide. For tasks where a smaller or faster model is sufficient, or where a different output modality is required, another model on api14 may fit better.