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What is Ministral 8B?

Mistral AI has introduced two advanced models tailored for on-device computing and edge applications, collectively known as "les Ministraux": Ministral 3B and Ministral 8B. These models are particularly remarkable for their abilities in knowledge retention, commonsense reasoning, function-calling, and overall operational efficiency, all while being under the 10B parameter threshold. With support for an impressive context length of up to 128k, they cater to a wide array of applications, including on-device translation, offline smart assistants, local analytics, and autonomous robotics. A standout feature of the Ministral 8B is its incorporation of an interleaved sliding-window attention mechanism, which significantly boosts both the speed and memory efficiency during inference. Both models excel in acting as intermediaries in intricate multi-step workflows, adeptly managing tasks such as input parsing, task routing, and API interactions according to user intentions while keeping latency and operational costs to a minimum. Benchmark results indicate that les Ministraux consistently outperform comparable models across numerous tasks, further cementing their competitive edge in the market. As of October 16, 2024, these innovative models are accessible to developers and businesses, with the Ministral 8B priced competitively at $0.1 per million tokens used. This pricing model promotes accessibility for users eager to incorporate sophisticated AI functionalities into their projects, potentially revolutionizing how AI is utilized in everyday applications.

What is Bonsai 27B?

Bonsai 27B emerges as the newest flagship in the Bonsai series, representing the first-ever 27B-class model crafted for mobile device functionality. Leveraging the foundation of Qwen3.6 27B, this model significantly enhances local device capabilities with sophisticated multi-step reasoning, structured tool interactions, vision tasks, and agentic loops that ensure coherence across numerous operations. The Bonsai 27B is offered in two unique versions, with the Ternary Bonsai 27B utilizing ternary weights alongside FP16 group-wise scaling to achieve an effective weight of 1.71 bits, while maintaining a 5.9 GB footprint ideal for high-performance laptops. Alternatively, the 1-bit Bonsai 27B adopts binary weights with the same group-wise scaling approach, resulting in an effective weight of 1.125 bits and a reduced size of 3.9 GB, which aligns well with the memory limitations of devices such as the iPhone 17 Pro. Both variants operate smoothly throughout the entire language network, encompassing embeddings, attention mechanisms, MLPs, and the language model head, without the need for higher-precision solutions. Additionally, they include a compact 4-bit vision tower, which empowers on-device workflows to accurately analyze screenshots, documents, and camera inputs, thereby improving user interaction and productivity. This groundbreaking methodology illustrates Bonsai 27B's dedication to advancing the frontiers of mobile AI technology and enhancing the user experience across diverse applications.

Media

Media

Integrations Supported

302.AI
APIPark
AiAssistWorks
AnythingLLM
BLACKBOX AI
BlueGPT
Continue
Deep Infra
EvalsOne
GMTech
Humiris AI
Kiin
Literal AI
Mammouth AI
Noma
Respan
Simplismart
WebLLM
Wordware

Integrations Supported

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Open source
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

iPhone
iPad
Mac

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

mistral.ai/news/ministraux/

Company Facts

Organization Name

PrismML

Date Founded

2026

Company Location

United States

Company Website

prismml.com/news/bonsai-27b

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

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