Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 1 Rating

Total
ease
features
design
support

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

Kimi K2.7 Code is a Moonshot AI coding model built to help developers handle software engineering, code generation, debugging, and agent-based development workflows. It focuses on long-horizon coding tasks, where an AI assistant needs to understand goals, work across many files, and complete multi-step development work. The model builds on the Kimi K2.6 architecture and is described as improving agentic capabilities while reducing thinking-token usage by about 30% compared with K2.6. Kimi K2.7 Code offers a 256K context window, which helps developers work with larger repositories, longer prompts, and more detailed project instructions. It can be accessed through Kimi Code, Moonshot’s API platform, and third-party model providers such as Together AI. The model also supports OpenAI- and Anthropic-compatible APIs, making it easier for teams to test it as a replacement or addition to existing coding assistant workflows. Developers who want to self-host or experiment with the model can access it through Hugging Face, where deployment guidance references vLLM, SGLang, and KTransformers. Kimi K2.7 Code is especially relevant for teams interested in open-source coding agents, long-context software tasks, and tool-integrated development. While some third-party commentary notes that benchmark claims should be reviewed carefully, the model is positioned as a strong option for developers seeking flexible, agentic coding support.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Brokk
C++
Claude Code
Claw Code
Cloudflare
EaseMate AI
Fireworks AI
Go
Java
JetBrains Junie
Kotlin
Kubernetes
LM Studio Bionic
Nebius Token Factory
Odysseus
OpenCode
Pi Agent
PowerShell
Vercel AI Gateway
XML

Integrations

Brokk
C++
Claude Code
Claw Code
Cloudflare
EaseMate AI
Fireworks AI
Go
Java
JetBrains Junie
Kotlin
Kubernetes
LM Studio Bionic
Nebius Token Factory
Odysseus
OpenCode
Pi Agent
PowerShell
Vercel AI Gateway
XML

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

Moonshot AI

Founded

2023

Country

China

Website

www.kimi.com

Product Features

Product Features

Alternatives

Alternatives

Bonsai 27B Reviews

Bonsai 27B

PrismML
Bonsai Image Reviews

Bonsai Image

PrismML
Big Pickle Reviews

Big Pickle

OpenCode Zen
Bonsai.io Reviews

Bonsai.io

One More Cloud
Kimi K3 Reviews

Kimi K3

Moonshot AI
Claude Fable 5 Reviews

Claude Fable 5

Anthropic