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What is North Mini Code?

North Mini Code marks the launch of Cohere's innovative agentic coding model, specifically designed for developers, and represents the initial offering in its next generation of advanced models. This compact and effective open-source solution is tailored for the independent developer community, providing exceptional software development capabilities without requiring extensive hardware resources. Utilizing a mixture-of-experts architecture, it features a total of 30 billion parameters, with 3 billion actively engaged, delivering powerful agentic coding functionalities in a streamlined format. The model is meticulously optimized for a variety of tasks, including code generation, agentic software engineering, and terminal operations, boasting an impressive context length of 256K and a maximum generation capacity of 64K. It is crafted with real-world developer practices in mind, allowing for the management of sub-agents, architecture mapping, code reviews, and supporting coding agents in overcoming complex software challenges. By integrating these capabilities, developers can significantly boost their productivity and efficiency in software development projects, making it an invaluable tool in their arsenal. As a result, North Mini Code not only facilitates better coding practices but also fosters a collaborative environment for developers to thrive.

What is Kimi K2 Thinking?

Kimi K2 Thinking is an advanced open-source reasoning model developed by Moonshot AI, specifically designed for complex, multi-step workflows where it adeptly merges chain-of-thought reasoning with the use of tools across various sequential tasks. It utilizes a state-of-the-art mixture-of-experts architecture, encompassing an impressive total of 1 trillion parameters, though only approximately 32 billion parameters are engaged during each inference, which boosts efficiency while retaining substantial capability. The model supports a context window of up to 256,000 tokens, enabling it to handle extraordinarily lengthy inputs and reasoning sequences without losing coherence. Furthermore, it incorporates native INT4 quantization, which dramatically reduces inference latency and memory usage while maintaining high performance. Tailored for agentic workflows, Kimi K2 Thinking can autonomously trigger external tools, managing sequential logic steps that typically involve around 200-300 tool calls in a single chain while ensuring consistent reasoning throughout the entire process. Its strong architecture positions it as an optimal solution for intricate reasoning challenges that demand both depth and efficiency, making it a valuable asset in various applications. Overall, Kimi K2 Thinking stands out for its ability to integrate complex reasoning and tool use seamlessly.

Media

Media

Integrations Supported

OpenCode

Integrations Supported

GPT-5
GPT-5.2 Instant
GPT-5.2 Pro
GPT-5.2 Thinking
GPT-5.3 Instant
GPT-5.4
GPT-5.4 Pro
GPT-5.4 mini
GPT-5.4 nano
GPT-5.5 Pro
GPT-5.6 Terra
GPT-6 Astra
GPT-6 Sol
GPT-6.1 Sol
Holo4
Hugging Face
OpenClaw
Oxlo.ai
Shiori

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Open source
Free Version

Supported Platforms

Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Cohere

Date Founded

2019

Company Location

Canada

Company Website

cohere.com/blog/north-mini-code

Company Facts

Organization Name

Moonshot AI

Date Founded

2023

Company Location

United States

Company Website

moonshotai.github.io/Kimi-K2/thinking.html

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Open-Weight AI Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Open-Weight AI Models

Not specified

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