GPT Audio
Neural Network
GPT Audio is an OpenAI speech synthesis model: an updated decoder provides natural sound and a stable voice.
Specifications
- Input
- text, documents
- Output
- text
- Context size
- 128 000 tokens
- Max answer length
- 16 384 tokens
- Capabilities
- function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT Audio?
GPT Audio is OpenAI's first public audio model: an updated decoder provides more natural voice sound and a stable timbre throughout the narration, without noticeable jumps between fragments. This is important where you need smooth sound in long materials rather than a one-off line. Through BotHub, the model works from Russia without a VPN or foreign card: you pay with a Russian card in rubles for actual tokens used, and they do not expire. Nearby, in one window, there are over 250 models—you can switch and compare without new accounts, and a unified OpenAI-compatible API allows you to connect GPT Audio to your product and change the model if necessary without rewriting the integration. Data is transmitted with AES-GCM encryption and is not saved, and companies have access to contracts, invoices, electronic document management, and an admin panel with limits. The model is useful if you are voicing training courses and videos, building a voice assistant with speech response, preparing audio versions of articles and newsletters, recording lines for interface prototypes, or turning finished scripts into podcasts.Frequently asked questions about GPT Audio
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-audio from OpenAI in BotHub works with text and documents: it answers questions, writes and edits texts, analyzes uploaded files, helps with code, and connects to external tools via function calling. Suitable for work correspondence, document analytics, and API scenarios.
In one response, the model can output up to 16,384 tokens—enough for a long article, detailed analysis, or a large code snippet. Keep in mind the 4,095-token context window: it limits the volume of what you send to the model along with the dialogue history.
A separate step-by-step reasoning mode is not noted in our data, but that doesn't mean it doesn't exist. In practice, a simple trick helps: ask the model in the prompt to break the task into steps and show the solution process—answers involving logic and calculations become more accurate.
Yes, function calling and structured JSON output are confirmed. The model decides when to call your tool and returns arguments in the specified schema. Convenient for agents, document parsing, and integrations: via the unified OpenAI-compatible BotHub API, this connects without rewriting code.
According to our data, documents are accepted as input in addition to text—you can upload a file and ask it to analyze, summarize, or extract the necessary data. The acceptance of images, audio, and video is not noted in our data, so for such tasks, it is more convenient to switch to a specialized model in the same interface.
Language characteristics are not specified in our data, so we will not promise specific accuracy. The BotHub interface and Telegram bot are in Russian, payment is in rubles, and no VPN or foreign card is needed—so the easiest way is to test the model on your real task.