OpenAI: GPT Astra Latest

GPT Astra Latest is a text model from OpenAI. It sits in the GPT Astra family, and the provider describes it as a model that always redirects to the latest model in that family. If you point an integration at this model id, you are tracking whatever OpenAI currently serves as the newest member of the Astra line rather than pinning a specific version. That makes it a reasonable default when you want to stay current without editing your code each time the family moves forward.

The model accepts text, images and files as input, and it produces text as output. Its context window is 1,050,000 tokens, which is large enough to hold very long documents alongside a conversation history, and the maximum output is 128,000 tokens. Because images and files are accepted on the input side, you can send a mix of prose, screenshots, diagrams or attached documents in the same request and get a single text response back.

Those capabilities point to a few practical patterns. Long context plus file input suits tasks like summarising or querying large document sets, contracts, codebases, log archives or research material without heavy chunking. Image input supports screenshot understanding, diagram reading and extracting information from visual material. The supported parameters include tools and tool choice, so you can build function calling and agent style workflows where the model decides when to call out to your own systems. Structured outputs and response format let you constrain replies to a schema for downstream parsing, and seed gives you a way to make sampling more reproducible.

You call it through api14's OpenAI-compatible API using the model id "~openai/gpt-astra-latest". The request parameters supported on this model are include_reasoning, max_completion_tokens, max_tokens, reasoning, reasoning_effort, response_format, seed, structured_outputs, tool_choice, tools and verbosity. If you already have an OpenAI client pointed at the api14 base URL, switching to this model is usually just a change to the model field. The reasoning and reasoning_effort settings let you trade latency for more deliberate answers, while verbosity and max_completion_tokens control how much the model writes.

One thing to weigh is the redirect behaviour. Because the id always points to the latest Astra model, output characteristics can shift when OpenAI updates the family, which matters if you need strict reproducibility across releases. The model also outputs text only, so anything requiring generated images, audio or embeddings needs a different model. If your workload is simple and small, a smaller context model may be cheaper and faster to run.