Ministral 8B 2512
Neural Network
Ministral 8B 2512 is a lightweight multimodal model from Mistral AI; connect the ministral api for text and image processing.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 262 144 tokens
- Max answer length
- 209 715 tokens
- Capabilities
- function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Ministral 8B 2512?
Ministral 8B 2512 is a Mistral AI model from the Ministral 3 family: a compact 8-billion parameter language model that also understands images. It holds a balanced position in the lineup, focusing on efficiency, making it suitable where processing speed and request volume matter more than heavy specialization. Through BotHub, the model is accessible from Russia without a VPN or foreign card: you pay in rubles only for tokens used, with no subscription, and unused balance does not expire. Other neural networks are available in the same window, allowing you to switch and compare answers without rewriting integrations, while a unified OpenAI-compatible API lets you embed Ministral 8B 2512 into your product. Chats are encrypted via AES-GCM; for companies, we offer contracts, invoices, EDI, and an admin panel with limits. In practice, the model is used for mass text processing and classification, data extraction from scans and screenshots, image description for catalogs, drafting emails and support responses, and as a fast layer in multimodal systems for simple queries.Frequently asked questions about Ministral 8B 2512
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 compact Mistral model for text: it answers questions, writes and edits text, helps with code, and analyzes documents. A context window of up to 262,144 tokens allows you to work with long materials and correspondence. Suitable for assistants, routine automation, and processing large datasets.
The model's output limit is very high — up to 209,715 tokens per response. This is enough for a detailed analysis, a large code file, a multi-page report, or a full document transcription without splitting the task into separate parts and stitching fragments together.
A dedicated reasoning mode is not noted in our data. However, you can ask the model to break down the task step-by-step directly in the prompt: this technique usually improves results for logic, math, and code debugging. Other models are available in BotHub for complex reasoning chains.
Yes, the model supports function calling and structured JSON output. This is convenient for agents, connecting external services and databases, and parsing documents into ready-made fields. Through the unified OpenAI-compatible BotHub API, integration is connected without rewriting code.
Images and documents are accepted as input: you can ask to describe an image, extract data from a scan, table, or invoice, or analyze a long file. Audio and video are not noted in our data — for such tasks, BotHub has specialized models in the same window.
Mistral models are traditionally multilingual and work confidently with Russian queries: they answer based on meaning, summarize documents, and help with correspondence. It is easy to check the quality on your own tasks — in BotHub, you pay per token used, without a subscription, and you can switch to another model if necessary.