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What is Kimi K2.7 Code?

Kimi K2.7 Code is an open-source agentic coding model from Moonshot AI designed for developers, engineering teams, and AI coding workflows that require long-context understanding and multi-step execution. It is built for real-world software engineering tasks, including code generation, code review, debugging, repository navigation, tool use, and long-horizon development work. The model is described by Moonshot AI as a coding-focused agentic model with stronger performance on complex coding tasks than earlier Kimi K2 releases. Kimi K2.7 Code supports a 256K context window, allowing it to process large codebases, technical requirements, logs, documentation, and multi-file development context in a single workflow. It is available through Kimi Code, which provides developer-oriented tools for using the model in coding tasks. The model can also be accessed through Moonshot’s API platform, where Kimi K2.7 Code and Kimi K2.7 Code Highspeed are offered alongside earlier Kimi models. For developers who want more control, Kimi K2.7 Code is listed on Hugging Face with deployment support for inference engines such as vLLM, SGLang, and KTransformers. It uses OpenAI- and Anthropic-compatible API options, helping teams connect it to existing applications, coding tools, and agent systems more easily. Third-party model listings describe it as using a 1T-parameter mixture-of-experts architecture with 32B active parameters, native INT4 quantization, and reduced thinking-token usage compared with Kimi K2.6. The model is designed to improve efficiency by using fewer reasoning tokens while still supporting demanding programming workflows. Kimi K2.7 Code is a strong fit for developers who want an open, long-context, tool-friendly AI model for software engineering automation and AI-assisted development.

What is CheapTokens?

CheapTokens provides a flexible pay-as-you-go API service designed specifically for developers working on AI agents, coding workflows, and applications that leverage open-weight language models. The platform showcases a diverse model catalog featuring families such as DeepSeek, GLM, and MiniMax. It offers API endpoints that are compatible with both OpenAI and Anthropic systems, facilitating seamless integration of existing tools for developers. With a CheapTokens API key, a base URL, and a model ID, developers can effortlessly connect to the available resources. Billing is based on a prepaid USD balance, charging distinct rates for input and output tokens, which removes the necessity for a monthly subscription model. Pricing details are clearly presented per million tokens utilized, ensuring transparency. Furthermore, the website provides extensive API documentation along with practical examples of requests and detailed integration guides tailored for various coding assistants and agent tools. This wealth of resources empowers developers to implement solutions effectively and efficiently. The combination of competitive pricing and ample support makes CheapTokens an attractive option for a wide range of developers in today's tech landscape.

Media

Media

No images available

Integrations Supported

APIFree
AiAssistWorks
Brokk
C++
Clarifai
Claw Code
Cline
Java
JetBrains Junie
Kimi
Kotlin
NVIDIA TensorRT
Novita AI
OpenClaw
OpenCode
Python
SiliconFlow
Tailwind CSS
Together AI
XML

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

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Moonshot AI

Date Founded

2023

Company Location

China

Company Website

www.kimi.com

Company Facts

Organization Name

CheapTokens

Date Founded

2026

Company Location

Ireland

Company Website

cheaptokens.dev/en/

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Open-Weight AI Models

Not specified

Categories and Features

LLM API

Not specified

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