Ministral 3B

Version: 1

Mistral AI•Last updated November 2025

Ministral 3B is a state-of-the-art Small Language Model (SLM) optimized for edge computing and on-device applications. As it is designed for low-latency and compute-efficient inference, it it also the perfect model for standard GenAI applications that have

Low latency

Agents

Reasoning

Models from Microsoft, Partners, and Community

Models from Microsoft, Partners, and Community models are a select portfolio of curated models both general-purpose and niche models across diverse scenarios by developed by Microsoft teams, partners, and community contributors

Managed by Microsoft: Purchase and manage models directly through Azure with a single license, world class support and enterprise grade Azure infrastructure
Validated by providers: Each model is validated and maintained by its respective provider, with Azure offering integration and deployment guidance.
Innovation and agility: Combines Microsoft research models with rapid, community-driven advancements.
Seamless Azure integration: Standard Azure AI Foundry experience, with support managed by the model provider.
Flexible deployment: Deployable as Managed Compute or Serverless API, based on provider preference.

Learn more about models from Microsoft, Partners, and Community

Key capabilities

About this model

Ministral 3B and Ministral 8B set a new frontier in knowledge, commonsense, reasoning, function-calling, and efficiency in the sub-10B category, and can be used or tuned to a variety of uses, from orchestrating agentic workflows to creating specialist task workers.

Key model capabilities

Knowledge & Commonsense

Model	MMLU	AGIEval	Winogrande	Arc-c	TriviaQA
Gemma 2 2B	52.4	33.8	68.7	42.6	47.8
Llama 3.2 3B	56.2	37.4	59.6	43.1	50.7
Ministral 3B	60.9	42.1	72.7	64.2	56.7
Mistral 7B	62.4	42.5	74.2	67.9	62.5
Llama 3.1 8B	64.7	44.4	74.6	46.0	60.2
Ministral 8B	65.0	48.3	75.3	71.9	65.5

Code and Math

Model	HumanEval (pass@1)	GSM8K (maj@8)
Gemma 2 2B	20.1	35.5
Llama 3.2 3B	29.9	37.2
Ministral 3B	34.2	50.9
Mistral 7B	26.8	51.3
Llama 3.1 8B	37.8	61.7
Ministral 8B	34.8	64.5

Chat/Arena (gpt-4o judge)

Model	MTBench	Arena Hard	Wild bench
Gemma 2 2B	7.5	51.7	32.5
Llama 3.2 3B	7.2	46.0	27.2
Ministral 3B	8.1	64.3	36.3
Mistral 7B	6.7	44.3	33.1
Llama 3.1 8B	7.5	62.4	37.0
Gemma 2 9B	7.6	68.7	43.8
Ministral 8B	8.3	70.9	41.3

Use cases

See Responsible AI for additional considerations for responsible use.

Key use cases

Our most innovative customers and partners have increasingly been asking for local, privacy-first inference for critical applications such as on-device translation, internet-less smart assistants, local analytics, and autonomous robotics. Les Ministraux were built to provide a compute-efficient and low-latency solution for these scenarios. From independent hobbyists to global manufacturing teams, les Ministraux deliver for a wide variety of use cases. Used in conjunction with larger language models such as Mistral Large, les Ministraux are also efficient intermediaries for function-calling in multi-step agentic workflows. They can be tuned to handle input parsing, task routing, and calling APIs based on user intent across multiple contexts at extremely low latency and cost.

Out of scope use cases

Prompts and completions are passed through a default configuration of Azure AI Content Safety classification models to detect and prevent the output of harmful content. Learn more about Azure AI Content Safety . Configuration options for content filtering vary when you deploy a model for production in Azure AI; learn more .

Pricing

Pricing is based on a number of factors, including deployment type and tokens used. See pricing details here.

Technical specs

Number of Parameters: 3,6 billions