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Description

Bonsai 27B stands as the latest multimodal flagship in the Bonsai lineup, marking the debut of a 27B-class model designed to operate on mobile devices. Built on the foundation of Qwen3.6 27B, it introduces an elevated level of capability for local devices, featuring advanced multi-step reasoning, structured tool interactions, vision tasks, and agentic loops for computer use that maintain coherence throughout multiple steps. The Bonsai 27B is available in two distinct variants. The Ternary Bonsai 27B employs ternary weights combined with FP16 group-wise scaling, achieving an effective weight of 1.71 bits and occupying a 5.9 GB footprint, suitable for high-performance laptop applications. In contrast, the 1-bit Bonsai 27B utilizes binary weights with identical group-wise scaling, resulting in an effective weight of 1.125 bits and a more compact 3.9 GB footprint, making it compatible with the memory constraints of devices like the iPhone 17 Pro. Both models operate seamlessly across the entire language network, including embeddings, attention mechanisms, MLPs, and the language model head, without resorting to higher-precision alternatives. They also feature a compact 4-bit vision tower, enabling on-device workflows to effectively interpret screenshots, documents, and camera inputs, enhancing user interaction and productivity. This innovative approach underscores Bonsai 27B's commitment to pushing the boundaries of mobile AI capabilities.

Description

Gemma 4 is an advanced AI model developed by Google as part of its Gemini architecture, designed to deliver strong performance while remaining accessible to developers. The model is optimized to run on a single GPU or TPU, allowing more organizations and researchers to experiment with powerful AI technology. Gemma 4 improves natural language understanding and generation, making it suitable for applications such as chatbots, text analysis, and automated content creation. Its architecture enables the model to process complex language patterns while maintaining efficient computational performance. Developers can integrate Gemma 4 into various AI projects that require intelligent text processing or conversational capabilities. The model is designed with scalability in mind, allowing it to support both research experiments and production systems. By offering high-performance AI in a more accessible format, Gemma 4 lowers the barrier for developing sophisticated AI solutions. Its flexibility makes it useful for industries ranging from technology and education to business automation. Researchers can also use the model to explore new AI techniques and improve language processing systems. Overall, Gemma 4 represents a step forward in making powerful AI models easier to deploy and use.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

No images available

Integrations

BLACKBOX AI
C#
C++
Clojure
Cloudflare AI Gateway
EmbeddingGemma
FriendliAI
Gemini
Gemini Enterprise
Gemini Enterprise Agent Platform
Google Colab
HTML
Kotlin
LFM2.5
Mirai
OpenCode
Ruby
SQL
Scala
kluster.ai

Integrations

BLACKBOX AI
C#
C++
Clojure
Cloudflare AI Gateway
EmbeddingGemma
FriendliAI
Gemini
Gemini Enterprise
Gemini Enterprise Agent Platform
Google Colab
HTML
Kotlin
LFM2.5
Mirai
OpenCode
Ruby
SQL
Scala
kluster.ai

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Open source
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

PrismML

Founded

2026

Country

United States

Website

prismml.com/news/bonsai-27b

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

deepmind.google/models/gemma/

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