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One year after launching Mistral 7B, the company unveils les Ministraux-Ministral 3B and 8B-for on-device computing, offering unmatched knowledge, commonsense reasoning, and efficiency in a compact package.
On the one-year anniversary of the release of Mistral 7B, which significantly advanced independent frontier AI innovation, Mistral AI is proud to introduce two new state-of-the-art models designed specifically for on-device computing and edge use cases. These models, named les Ministraux-Ministral 3B and Ministral 8B-are poised to set a new standard in knowledge, commonsense reasoning, function-calling, and efficiency within the sub-10B category.
Key Features:
Les Ministraux are designed to address the growing demand for local, privacy-first inference. Here are some key use cases:
These models can also serve as efficient intermediaries for function-calling in multi-step agentic workflows. They can be fine-tuned to handle input parsing, task routing, and API calls based on user intent across multiple contexts at extremely low latency and cost.

To demonstrate the performance of les Ministraux, Mistral AI conducted a series of evaluations using their internal framework for fair comparison. Here are some highlights:
Both Ministral 3B and Ministral 8B are available starting today. Here’s the pricing on la Plateforme:
| Model | API | Pricing on la Plateforme | License | |----------------|------------------------|--------------------------|-----------------------------------| | Ministral 8B | ministral-8b-latest | $0.1 / M tokens (input and output) | Mistral Commercial License |
Les Ministraux-Ministral 3B and Ministral 8B-are significant advancements in edge models, offering a blend of efficiency, performance, and privacy. Whether you're an independent hobbyist or part of a global manufacturing team, these models are designed to meet your on-device computing needs.
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About the author
Kai built ML infrastructure at a Bay Area startup before developing an obsession with transformer architectures and inference optimisation that eventually pulled him out of product work entirely. A stint at a compute research lab sharpened his instinct for what actually matters in a model release versus what is marketing. He writes from the inside — from the perspective of someone who has debugged the systems he is describing at three in the morning. He is allergic to hype and instinctively drawn to the unglamorous plumbing questions that everyone else skips over.
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