GPT 5 Mini
Neural Network
GPT-5 Mini is a compact version of OpenAI's GPT-5 with lower latency; GPT 5 Mini API for reasoning tasks.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 400 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- minimal, low, medium, high
- Capabilities
- reasoning, function calling, Batch API
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT 5 Mini?
GPT-5 Mini is a compact version of OpenAI's GPT-5, designed for lighter reasoning tasks. It retains the larger model's approach to following instructions and safety settings but responds with lower latency and is more cost-effective, making it suitable where response speed and request volume are priorities. In BotHub, the model works without a VPN or foreign card; payment is made with Russian cards in rubles and charged based on actual token usage. Over 250 other neural networks are available in the same window, making it easy to compare answers for a single query, and a unified OpenAI-compatible API allows you to switch models in calls without rewriting integrations. Companies have access to contracts, invoices, electronic document management (EDO), and an admin panel with limits. Simple scenarios include: chat assistants and support with high request volumes, drafting emails and documents, summarizing and structuring long materials, labeling and classifying incoming requests, and acting as a fast layer in multimodal services where you delegate the most complex steps to larger models.Frequently asked questions about GPT 5 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-mini is an OpenAI text model with a 400,000 token context. It is suitable for working with code, analyzing large documents and images, analytics, and tasks requiring sequential reasoning. It accepts text, documents, and images as input, can call tools, and integrate into your services via API.
Up to 128,000 tokens in a single response — that's dozens of pages. Enough for a voluminous document, detailed instruction, or an entire code module. The verbosity parameter allows you to adjust the length: from a short summary to a maximally detailed step-by-step analysis.
Yes, reasoning before answering is supported: the model builds a chain of thought before providing a result. Through the effort parameter, you set the depth of deliberation — faster and more economical for simple queries, more thorough for STEM tasks, logic, and code debugging.
Yes. Function calling and structured JSON output are confirmed, so the model can be connected to external tools, databases, and your own services. BotHub uses a unified OpenAI-compatible API: you can switch models in a multimodal system without rewriting the integration.
Images and documents — yes, they can be sent as input along with text: scans, contracts, diagrams, or interface screenshots. There is no mention of audio or video in our data, so please check with your own scenario — all models are available in one window.
The language of prompts and responses is not specifically described in our data, so we won't make exact promises — it's more reliable to test the model with your own texts. In BotHub, it takes a minute: access from Russia without a VPN and payment with Russian cards based on actual token usage.