Kimi K2.7 Code

Kimi K2.7 Code

Moonshot AI
SubQ Snap

SubQ Snap

Subquadratic
+
+

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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

SubQ Snap is a long-context decision model for enterprise and agentic workflows, built to make structured decisions quickly over large amounts of information. It handles tasks such as choosing which files are relevant, selecting the next tool, checking whether a result passes, deciding whether a workflow should continue, and determining when a frontier model is needed. Instead of generating open-ended text, Snap takes context, a question, and a finite set of allowed answers, then returns a probability distribution over those answers. It supports up to 384K tokens of mixed text and image context, allowing it to reason over codebases, contracts, interaction histories, logs, screenshots, charts, diagrams, and scanned pages in a single call. Powered by Subquadratic Sparse Attention, Snap reduces the cost of reading long inputs while a decision head maps contextual representations directly to admissible answers without autoregressive generation.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

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

Developers and enterprise AI teams interested in a tool to make fast, structured decisions across long documents, codebases, multimodal inputs, and agentic workflows

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Open source
Free Version Supported
Free Trial Not Supported

Pricing

$0.05 per million input tokens
Free Version Not Supported
Free Trial Supported

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 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

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.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Moonshot AI
Founded: 2023
China
www.kimi.com

Company Information

Subquadratic
Founded: 2024
United States
subq.ai/introducing-subq-snap

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Categories

AI Coding Models Supported
AI Models Supported

Categories

AI Decision Models Supported

Integrations

C++ Supported
CSS Supported
Claw Code Supported
ClinePass Supported
Dart Supported
HTML Supported
JavaScript Supported
Kimi Work Supported
Kotlin Supported
Kubernetes Supported
Lua Supported
NVIDIA TensorRT Supported
Ollama Supported
OpenTag Supported
PrivatClaw Supported
Ruby Supported
SQL Supported
Solidity Supported
YAML Supported
ZooClaw Supported

Integrations

C++ Not Supported
CSS Not Supported
Claw Code Not Supported
ClinePass Not Supported
Dart Not Supported
HTML Not Supported
JavaScript Not Supported
Kimi Work Not Supported
Kotlin Not Supported
Kubernetes Not Supported
Lua Not Supported
NVIDIA TensorRT Not Supported
Ollama Not Supported
OpenTag Not Supported
PrivatClaw Not Supported
Ruby Not Supported
SQL Not Supported
Solidity Not Supported
YAML Not Supported
ZooClaw Not Supported
Claim Kimi K2.7 Code and update features and information
Claim Kimi K2.7 Code and update features and information
Claim SubQ Snap and update features and information
Claim SubQ Snap and update features and information