Ministral 8B 2512
Neural Network
Ministral 8B 2512 is a lightweight Mistral AI model from the Ministral 3 family with support for image inputs.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Ministral 8B 2512?
Ministral 8B 2512 is a balanced model from the Ministral 3 family by Mistral AI: a compact language model that understands both text and images. Its small size means fast responses and cost-efficiency for streaming tasks, while the batch processing variant is designed for large queues where real-time results aren't required. In BotHub, you work with the model without VPN or foreign cards, pay with a local card only for tokens used rather than a subscription, and tokens do not expire. Other neural networks are available in the same window, allowing you to compare responses and switch to a larger model without rewriting integrations: everything runs via a unified OpenAI-compatible API, and data is transmitted encrypted. It is useful for labeling and classifying large volumes of requests, extracting information from screenshots and document photos, generating draft descriptions from images, covering a low-cost layer in multimodal scenarios, or prototyping products before switching to a heavier model. For companies, contracts, invoices, electronic document management, and an admin panel with team limits are available.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 text model with tool support: it writes and edits text, analyzes documents and images, and helps with code and structured responses. Batch mode is suitable when you need to process a large volume of similar requests without urgency.
The context window is 262,144 tokens, and the model outputs up to 209,715 tokens per response. This is enough for a long report, a series of descriptions, or a detailed analysis of a large document in its entirety, without manual splitting and subsequent merging.
A separate reasoning mode is not noted in our data, so we will not deny it. In practice, a simple trick helps: ask in the prompt to break down the task step-by-step and show the thought process before the final conclusion.
Yes, function calling and structured JSON output are supported. The model accesses your tools and returns the response according to a specified schema, making it easy to integrate into agents and workflows via the unified OpenAI-compatible BotHub API.
Our data indicates support for images and documents in addition to text: you can send a scan, diagram, or file and ask to analyze the content. There is no mention of audio or video, so for such formats, it is better to choose a specialized model in the same window.
There is no specific data on languages in the model card, so we cannot provide guarantees. It is more reliable to test it with your own task: in BotHub, models are available in one window without VPN or foreign cards, and you can switch to another without rewriting integrations.