Kimi K2.7 Code

Kimi K2.7 Code

Moonshot AI
MAI-Code-1.1-Flash

MAI-Code-1.1-Flash

Microsoft AI
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About

Kimi K2.7 Code is an open-source, coding-focused agentic AI model developed by Moonshot AI for long-horizon software engineering tasks. It is designed to improve coding performance, agent workflows, and real-world development assistance compared with earlier Kimi K2 versions. The model supports a 256K context window, making it useful for working with large codebases, long technical documents, and complex multi-step programming tasks. Kimi K2.7 Code is available through Kimi Code and API access, with OpenAI- and Anthropic-compatible options for easier integration into developer workflows. It is also listed on Hugging Face and supports deployment through inference engines such as vLLM, SGLang, and KTransformers. With improved agentic capabilities, long-context support, and reduced thinking-token usage compared with K2.6, Kimi K2.7 Code gives developers a flexible open-source option for AI-assisted coding.

About

MAI-Code-1.1-Flash is a small, efficient coding model designed to help engineering teams write better code faster. Now in production in GitHub Copilot and built into VS Code, it focuses on real-world developer workflows, with particular improvements for command-line tasks and .NET development based on developer feedback. Compared with the version introduced at Microsoft Build in June, the model produces higher-quality code while using fewer tokens and streaming responses faster. Microsoft reports a 22% improvement on Terminal-Bench 2.1 in GitHub Copilot CLI and a 15% improvement on .NET tasks. Production results also showed a 4% increase in code survival and a 9% increase in return visits. In GitHub Copilot, tokens stream 25% faster and the model uses 25% fewer tokens to complete a task, aiming to deliver faster answers, less waiting, and more useful work from every token. Its gains come from improved training and serving efficiency, with optimization centered on real-world use.

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

Kimi K2.7 Code is best suited for software developers, engineering teams, AI coding tool builders, open-source model users, DevOps teams, and organizations that need long-context code generation, debugging, repository analysis, and agentic software engineering support

Audience

Software engineering teams and developers seeking to write and complete code faster with an efficient AI coding model integrated into their development workflow

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

Free
Open source
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Reviews/Ratings

Overall 4.0 / 5
features 4.0 / 5

Pros & Cons from Real Users

Pros

  • Kimi K2.7 Code has been a great model for coding and AI agent development. It handles technical prompts well, understands developer workflows, and gives clear, useful responses for real coding tasks. I use it for debugging, writing scripts, improving code structure, and planning agent workflows. It is especially helpful when I need clean reasoning, practical suggestions, and code that is easy to adapt. For AI agents, Kimi K2.7 Code feels reliable and capable. It does a strong job following instructions, working through multi-step tasks, and producing structured outputs that fit automation and agent-based use cases.

Cons

  • It still works best when the prompt includes enough context. For very complex projects or large codebases, I sometimes need to provide extra details to get the best results. I also prefer to review important code before using it, especially for production work, since small mistakes can still happen.

Pros & Cons from Real Users

Pros

  • The agentic coding angle is the best part. It can plan, reason, and execute across coding tasks, which makes it useful beyond simple autocomplete. I also like the screenshot-to-prototype feature. Being able to understand screenshots, diagrams, and designs could save a lot of time when turning UI ideas into working code.

Cons

  • The main downside is that I would still review everything carefully. Even a strong coding model can make bad assumptions, miss edge cases, or produce code that looks right but fails in a real project.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Moonshot AI
Founded: 2023
China
www.kimi.com

Company Information

Microsoft AI
Founded: 2024
United States
microsoft.ai/news/mai-code-1-1-flash-br-better-faster-at-a-quarter-of-the-cost/

Alternatives

Claude Fable 5

Claude Fable 5

Anthropic

Alternatives

Grok 4.6

Grok 4.6

SpaceXAI
Claude Mythos 5

Claude Mythos 5

Anthropic
Claude Fable 5

Claude Fable 5

Anthropic
Claude Sonnet 5

Claude Sonnet 5

Anthropic
Claude Mythos 5

Claude Mythos 5

Anthropic
Kimi K3

Kimi K3

Moonshot AI
MAI-Code-1-Flash

MAI-Code-1-Flash

Microsoft AI
Kimi K2.5

Kimi K2.5

Moonshot AI

Categories

Categories

Integrations

.NET
Visual Studio Code
C#
Claw Code
Cline
ClinePass
Dart
GitHub Copilot
HTML
Kimi Work
Kotlin
NVIDIA TensorRT
Nebius Token Factory
Novita AI
Ollama
OpenAI Codex
OpenCode
PHP
PowerShell
Together AI

Integrations

.NET
Visual Studio Code
C#
Claw Code
Cline
ClinePass
Dart
GitHub Copilot
HTML
Kimi Work
Kotlin
NVIDIA TensorRT
Nebius Token Factory
Novita AI
Ollama
OpenAI Codex
OpenCode
PHP
PowerShell
Together AI
Claim Kimi K2.7 Code and update features and information
Claim Kimi K2.7 Code and update features and information
Claim MAI-Code-1.1-Flash and update features and information
Claim MAI-Code-1.1-Flash and update features and information