Bonsai 27B

Bonsai 27B

PrismML
LFM2.5

LFM2.5

Liquid AI
+
+

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About

Bonsai 27B is the new multimodal flagship of the Bonsai family and the first 27B-class model to run on a phone. Based on Qwen3.6 27B, it brings a new capability tier to local devices: multi-step reasoning, structured tool calls, vision tasks, and computer-use agentic loops that stay coherent across many steps. Bonsai 27B comes in two variants. Ternary Bonsai 27B uses ternary weights with FP16 group-wise scaling, giving 1.71 effective bits per weight and a 5.9 GB footprint for the quality-oriented laptop-class version. 1-bit Bonsai 27B uses binary weights with the same group-wise scaling, giving 1.125 effective bits per weight and a 3.9 GB footprint that fits within the memory budget of an iPhone 17 Pro. Both variants run end-to-end across the language network, embeddings, attention, MLPs, and LM head with no higher-precision escape hatches. They are multimodal, with a compact 4-bit vision tower, so on-device workflows can understand screenshots, documents, and camera input.

About

Liquid AI’s LFM2.5 is the next generation of on-device AI foundation models designed to deliver high-performance, efficient AI inference on edge devices such as phones, laptops, vehicles, IoT systems, and embedded hardware without relying on cloud compute. It extends the previous LFM2 architecture by significantly increasing the pretraining scale and reinforcement learning stages, yielding a family of hybrid models around 1.2 billion parameters that balance instruction following, reasoning, and multimodal capabilities for real-world agentic use cases. The LFM2.5 family includes Base (for fine-tuning and customization), Instruct (general-purpose instruction-tuned), Japanese-optimized, Vision-Language, and Audio-Language variants, all optimized for fast, on-device inference under tight memory constraints and available as open-weight models deployable via frameworks like llama.cpp, MLX, vLLM, and ONNX.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Mobile AI developers who need a local multimodal model for private on-device reasoning, tool use, vision, and agentic workflows

Audience

Developers and organizations building on-device AI applications and intelligent agents that need efficient, high-quality AI models capable of running locally on consumer, edge, or embedded hardware

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

PrismML
Founded: 2026
United States
prismml.com/news/bonsai-27b

Company Information

Liquid AI
Founded: 2023
United States
www.liquid.ai/blog/introducing-lfm2-5-the-next-generation-of-on-device-ai

Alternatives

Bonsai Image

Bonsai Image

PrismML

Alternatives

MedGemma

MedGemma

Google DeepMind
Bonsai.io

Bonsai.io

One More Cloud
HunyuanOCR

HunyuanOCR

Tencent
GroupWise to Office 365 Migration

GroupWise to Office 365 Migration

Shoviv Software Pvt. Ltd.
Qwen2

Qwen2

Alibaba

Categories

Categories

Integrations

Amazon Bedrock
ElevenLabs
Gemma 3
Gemma 4
Hugging Face
LEAP
Llama
Llama 3.2
Qwen3

Integrations

Amazon Bedrock
ElevenLabs
Gemma 3
Gemma 4
Hugging Face
LEAP
Llama
Llama 3.2
Qwen3
Claim Bonsai 27B and update features and information
Claim Bonsai 27B and update features and information
Claim LFM2.5 and update features and information
Claim LFM2.5 and update features and information