Ministral 14B 2512
Neural Network
Ministral 14B is a compact Mistral AI language model for text tasks and integrations via the Ministral 14B API.
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 14B 2512?
Ministral 14B is the senior model in the Ministral 3 family from Mistral AI. Despite its compact size, it performs at a level comparable to the larger Mistral Small 3.2 24B, making it ideal where a balance of quality and speed is required. Via BotHub, the model is accessible without a VPN or foreign card: pay in rubles with a Russian card only for tokens used, not a subscription, and unused tokens do not expire. Access over 250 other neural networks in the same window to easily switch between them and compare answers for the same task. A unified OpenAI-compatible API allows you to switch models in your service without rewriting integrations. Chats are encrypted via AES-GCM, data is not saved, and companies have access to contracts, invoices, EDI, and an admin panel with employee limits. Use Ministral 14B for streaming text tasks: summarizing documents and correspondence, drafting support responses, and extracting structured data from free-form descriptions. It also serves as a fast layer in a multimodal pipeline, handling routine tasks while larger models process complex requests.Frequently asked questions about Ministral 14B 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 Mistral text model with a 262,144 token context. It is suitable for working with long documents and large code files, writing and refactoring, debugging, analytical summaries, and reasoning on STEM tasks. It accepts not only text but also images and documents as input.
The output limit is up to 209,715 tokens per response, which is very high for text models. It is enough for a detailed analysis of a large document, voluminous technical documentation, or a long code module without splitting the task into dozens of requests.
A separate hidden reasoning mode is not noted in our data. However, you can ask the model to write out the solution step-by-step, check against the conditions, and show intermediate conclusions directly in the prompt — this works well for STEM tasks and code debugging.
Yes, the model supports function calling and structured JSON output. This is convenient for agents, parsing documents into a specified schema, and integrating with your services. A unified OpenAI-compatible API is available in BotHub, so connection requires minimal changes.
Images and documents — yes: you can send a screenshot, diagram, table, or file and get a text analysis. Audio and video input are not noted in our data. If you need to work with sound, switch to a specialized model in the same BotHub window.
Mistral models are historically multilingual, and they understand Russian confidently. There are no exact measurements by language in our data, so the best way is to test it with your own prompts. Payment in rubles, access without VPN or foreign cards, and you can compare answers with another model in one window.