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What is MAI-Code-1.1-Flash?

MAI-Code-1.1-Flash is a streamlined and powerful coding model designed to boost both the speed and quality of code development specifically for engineering teams. Currently utilized in GitHub Copilot and seamlessly integrated into VS Code, it aligns with the everyday workflows of developers by particularly enhancing command-line functions and .NET operations based on user interactions. In comparison to the version revealed at Microsoft Build in June, this model demonstrates notable advancements in code quality, achieved through lower token consumption and faster streaming responses. Microsoft reports a 22% improvement on Terminal-Bench 2.1 for GitHub Copilot CLI, as well as a 15% enhancement in .NET task performance. Furthermore, production metrics reveal a 4% increase in code survival rates and a 9% rise in user retention on the platform. Impressively, within GitHub Copilot, tokens are streamed 25% more quickly, and the model utilizes 25% fewer tokens to complete tasks, which results in faster responses, shortened wait times, and heightened productivity from each token processed. These improvements arise from refined training approaches and enhanced operational efficiencies, with particular emphasis on practical application in real-world contexts. Ultimately, MAI-Code-1.1-Flash signifies a remarkable advancement in coding assistance technology, paving the way for more efficient development practices. With its emphasis on user experience and real-time feedback, this model is set to redefine how developers interact with coding tools.

What is Kimi K3?

Kimi K3 is Moonshot AI’s most advanced model, designed for high-end reasoning, software engineering, multimodal understanding, knowledge work, and agentic AI applications. The model has 2.8 trillion parameters and is built on Kimi Delta Attention, a hybrid linear attention mechanism created for long-context performance. It also uses Attention Residuals and supports a native context window of up to 1 million tokens. This makes Kimi K3 suitable for tasks involving large codebases, long research materials, enterprise documentation, multi-file analysis, legal documents, technical manuals, and complex workflows. Kimi K3 always has thinking mode enabled, with reasoning effort configured through the reasoning_effort field and maximum effort currently supported as the default. Developers can use the model through an OpenAI-compatible API, making it easier to integrate with existing SDKs, clients, and application infrastructure. The model supports streaming responses with separate reasoning and final-answer deltas, allowing applications to display reasoning progress and final content differently. Kimi K3 also supports strict structured output with JSON Schema, partial mode for continuing from a prefix, custom tool calling, required tool use, and dynamic tool loading through system messages. Its vision capabilities support image and video inputs through base64 or uploaded files, enabling analysis of visual content alongside text. Automatic context caching helps workflows that reuse long prefixes, such as large knowledge bases or persistent system context, without requiring developers to manage cache IDs manually. By combining frontier-scale parameters, long-context processing, visual input, structured outputs, tool orchestration, and developer-friendly API compatibility, Kimi K3 gives teams a strong foundation for advanced AI agents, coding assistants, research systems, enterprise automation, and multimodal applications.

Media

Media

Integrations Supported

.NET
Visual Studio Code
APIFree
C#
CSS
Cerebras
Cline
Command Code
Go
HTML
Hermes Agent
Java
Kimi
Kimi Code CLI
OpenAI Codex
PrivatClaw
Python
R
Vercel AI Gateway
ZooClaw

Integrations Supported

.NET
Visual Studio Code
APIFree
C#
CSS
Cerebras
Cline
Command Code
Go
HTML
Hermes Agent
Java
Kimi
Kimi Code CLI
OpenAI Codex
PrivatClaw
Python
R
Vercel AI Gateway
ZooClaw

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

$3 per 1M tokens (input)
Kimi K3 is priced per 1 million tokens:

Cached input: $0.30
Uncached input: $3.00
Output: $15.00
Context window: 1,048,576 tokens

Cached inputs cost 90% less than uncached inputs, while generated output is the most expensive token category. Prices exclude applicable taxes, which are calculated based on the customer’s jurisdiction.
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Microsoft AI

Date Founded

2024

Company Location

United States

Company Website

microsoft.ai/news/mai-code-1-1-flash-br-better-faster-at-a-quarter-of-the-cost/

Company Facts

Organization Name

Moonshot AI

Date Founded

2023

Company Location

China

Company Website

kimi.ai

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