GPT 4.1 Mini Batch
Neural Network
GPT 4.1 Mini is an OpenAI model with 1M token context: gpt 4.1 mini api for code, reasoning, and batch processing.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 047 576 tokens
- Max answer length
- 32 768 tokens
- Capabilities
- function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT 4.1 Mini Batch?
GPT 4.1 Mini is a mid-sized OpenAI model comparable in quality to GPT-4o, but faster and more cost-effective. It retains a 1M token context window, allowing large documents, logs, and entire code repositories to fit in a single request. The batch version is designed for bulk processing: send large sets of tasks and retrieve results without manual queuing. In BotHub, the model is accessible from Russia without a VPN or foreign card; payment is made in rubles via Russian cards for actual token usage, and tokens do not expire. Over 250 other neural networks are available in the same window, making it easy to switch and compare responses. A unified OpenAI-compatible API allows connecting GPT 4.1 Mini to your services and switching models without rewriting integrations. For companies, we offer contracts, invoices, and electronic document management. Use cases include: mass data labeling and classification, code generation and refactoring with debugging, parsing long documents and correspondence, structured data extraction via function calling, and chatbots/assistants where response speed is critical.Frequently asked questions about GPT 4.1 Mini Batch
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.
This is a text model with a context window of about 1,047,576 tokens. It is suitable for coding, refactoring, debugging, analyzing large documents, summarization, STEM tasks, and analytics. The batch mode is convenient for mass data processing when you need volume rather than instant responses.
The output limit is 32,768 tokens per response. This is enough for a lengthy article, detailed document analysis, a large code module, or a series of related fragments. For longer materials, break the task into parts: the 1,047,576 token context is sufficient for the model to remember previous blocks.
A separate reasoning mode is not noted for this model in our data. However, you can ask it to write out the solution step-by-step in the prompt, and it will break down the task logic. If you specifically need reasoning models, you can easily switch to another one from the BotHub catalog.
Yes, the model supports function calling and structured JSON output. This allows connecting it to external services, databases, and agent scenarios, ensuring a predictable response format. You can work via the unified OpenAI-compatible BotHub API without rewriting integrations when switching models.
The model accepts text, images, and documents as input, including native file processing. You can provide a screenshot of an interface, a diagram, a table, or a PDF and ask it to analyze the content. Audio and video are not noted in our data; the model generates text only.
The GPT-4.1 series models are trained on multilingual data and work confidently with Russian queries and documents. We do not have specific language benchmarks, so please evaluate the quality on your task. Access to the model in BotHub is open from Russia without a VPN or foreign card; payment is in rubles.