Activefastllm Open Source

Ministral 3B

by Mistral AI· Released October 2024

Ministral 3B is a small, efficient language model designed for on-device and edge computing applications. It offers strong performance for its size, with a 128K token context window and support for function calling, making it suitable for low-latency, privacy-sensitive tasks.

Official Site API Docs 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

128K tokens

Max output

—

Modalities

text

Parameters

License

Apache-2.0

Capabilities

Function CallingStreamingJSON ModeCode GenerationMultilingual

Best For

On-device and edge applications requiring low latency and privacy, such as mobile assistants and embedded systems.

Strengths

Very small model size (3B parameters) enabling deployment on resource-constrained devices
128K token context window, unusually large for a model of this size
Supports function calling and JSON mode for structured outputs
Open source under Apache 2.0 license

Limitations

Limited reasoning and factual accuracy compared to larger models
Not suitable for complex multi-step tasks or advanced coding
Smaller vocabulary and less nuanced understanding than frontier models

Use Cases

On-device chatbots and virtual assistants

Real-time text summarization on mobile devices

Edge-based data extraction and classification

Privacy-preserving local inference for sensitive data

Embedded systems for IoT and smart devices

Educational tools and lightweight tutoring systems

Prototyping and rapid iteration for smaller-scale NLP tasks

Improvements Over Previous Model

First model in the Ministral family, so no direct predecessor; compared to other small models, it offers a much larger context window (128K vs typical 4K-32K)
Open source under Apache 2.0, unlike many proprietary small models
Supports function calling and JSON mode, features often absent in models of this size

Back to all models

Activefastllm Open Source

Ministral 3B

by Mistral AI· Released October 2024

Official Site API Docs 🤗 Hugging Face

Input cost

Free (open source)

Output cost

Free (open source)

Context window

128K tokens

Max output

—

Modalities

text

Parameters

License

Apache-2.0

Capabilities

Function CallingStreamingJSON ModeCode GenerationMultilingual

Best For

On-device and edge applications requiring low latency and privacy, such as mobile assistants and embedded systems.

Strengths

Very small model size (3B parameters) enabling deployment on resource-constrained devices
128K token context window, unusually large for a model of this size
Supports function calling and JSON mode for structured outputs
Open source under Apache 2.0 license

Limitations

Limited reasoning and factual accuracy compared to larger models
Not suitable for complex multi-step tasks or advanced coding
Smaller vocabulary and less nuanced understanding than frontier models

Use Cases

On-device chatbots and virtual assistants

Real-time text summarization on mobile devices

Edge-based data extraction and classification

Privacy-preserving local inference for sensitive data

Embedded systems for IoT and smart devices

Educational tools and lightweight tutoring systems

Prototyping and rapid iteration for smaller-scale NLP tasks

Improvements Over Previous Model

First model in the Ministral family, so no direct predecessor; compared to other small models, it offers a much larger context window (128K vs typical 4K-32K)
Open source under Apache 2.0, unlike many proprietary small models
Supports function calling and JSON mode, features often absent in models of this size

Back to all models