Average Ratings 1 Rating

Total
ease
features
design
support

Average Ratings 1 Rating

Total
ease
features
design
support

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.

Description

SWE-1.7 is Cognition’s most capable software engineering model, built to push frontier coding performance while reducing the cost of high-quality agentic rollouts. The model is designed for real-world software development tasks that require extended reasoning, codebase understanding, terminal use, debugging, feature work, migrations, and careful validation. It was trained from a Kimi K2.7 base and improved through Cognition’s reinforcement learning pipeline, including more stable training, stronger infrastructure, better data curation, and long-horizon task techniques. SWE-1.7 is especially optimized for asynchronous software engineering, where an agent needs to work through large projects over longer sessions instead of simply answering short prompts. Its self-compaction capabilities allow the model to summarize its working state and resume from that summary, helping it operate beyond the raw context window on multi-hour tasks. The model is also trained to balance task success with efficiency, using concise reasoning when possible while preserving deeper exploration for harder problems. SWE-1.7 tends to investigate codebases more thoroughly than its base model, reading files, running searches, probing edge cases, and experimenting before making changes. It is available in Devin through web, desktop, and CLI interfaces, with Cerebras serving support at 1000 TPS. SWE-1.7 gives developers and engineering teams a high-performance coding model for complex software projects at a more practical cost.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

C# Yes 
C++ Yes 
CSS Yes 
Cerebras Yes 
Dart Yes 
Go Yes 
JavaScript Yes 
Kotlin Yes 
Kubernetes Yes 
Lua Yes 
Objective-C Yes 
PHP Yes 
PowerShell Yes 
Python Yes 
R Yes 
Ruby Yes 
Rust Yes 
SQL Yes 
Scala Yes 
Swift Yes 

Integrations

C# Yes 
C++ Yes 
CSS Yes 
Cerebras Yes 
Dart Yes 
Go Yes 
JavaScript Yes 
Kotlin Yes 
Kubernetes Yes 
Lua Yes 
Objective-C Yes 
PHP Yes 
PowerShell Yes 
Python Yes 
R Yes 
Ruby Yes 
Rust Yes 
SQL Yes 
Scala Yes 
Swift Yes 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

$20/month
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Moonshot AI

Founded

2023

Country

China

Website

www.kimi.com

Vendor Details

Company Name

Cognition

Founded

2023

Country

United States

Website

cognition.com

Product Features

Product Features

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Alternatives

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