GPT 5.1 Codex Mini
Neural Network
GPT-5.1-Codex-Mini is a smaller, faster version of OpenAI's GPT-5.1-Codex for coding tasks.
Max answer length
(in tokens)
Context size
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Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT 5.1 Codex Mini?
GPT-5.1-Codex-Mini is an OpenAI model from the Codex line, focused on coding. It differs from GPT-5.1-Codex by being smaller and faster, making it ideal for scenarios requiring quick response times and high volumes of similar requests. In BotHub, the model is accessible without a VPN or foreign card: top up your balance with a Russian card and pay per token; unused tokens do not expire. Access over 250 models in one window to compare responses for the same task. A unified OpenAI-compatible API allows you to switch models in the multi-model service without rewriting integrations. Requests are transmitted with AES-GCM encryption. Practically, the model is useful for quickly analyzing third-party modules, drafting function tests, debugging stack traces, refactoring large files, or embedding code suggestions into editors and internal team tools. For companies, BotHub provides contracts, invoices, and electronic document management, with an admin panel to manage employee access and set limits.Frequently asked questions about GPT 5.1 Codex Mini
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
gpt-5.1-codex-mini is an OpenAI Codex model focused on coding: writing functions, refactoring, analyzing third-party repositories, debugging, and explaining logic. It is also useful for technical documentation, log analysis, and tasks requiring reasoning and careful step-by-step conclusions.
The output limit is 128,000 tokens per response, enough for a large code module, detailed analysis, or long documentation. The context window is 400,000 tokens, so large files and previous correspondence fit in the dialogue along with the response.
Yes, reasoning before answering is supported: the model builds a chain of thought first, then provides the result. Settings for reasoning depth and response detail are available, so you can get simple edits quickly and allocate more computation for architectural tasks and debugging.
Yes. The model calls functions and returns structured JSON according to a specified schema, making it easy to integrate into agents, internal services, and CI scenarios. In BotHub, this works via a unified OpenAI-compatible API: you can switch models without rewriting integrations.
Images and documents — yes: you can send a screenshot of an error, an interface diagram, or a specification file and get a text analysis. Audio and video support is not noted in our data, so for voiceover and video processing, choose specialized models in BotHub.
We do not have specific data on the quality of Russian for this model, so we won't make promises — it's easier to check with your own task: send a typical request and compare the result with other models in one window. The BotHub interface is in Russian, payment is in rubles, and no VPN or foreign card is needed.