Average Ratings 1 Rating

Total
features

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

MAI-Code-1.1-Flash is a compact and effective coding model aimed at enhancing the speed and quality of code development for engineering teams. Currently implemented in GitHub Copilot and integrated into VS Code, it caters to the actual workflows of developers, specifically enhancing command-line operations and .NET tasks based on user input. When compared to the version unveiled at Microsoft Build in June, this model showcases a significant improvement in code quality, achieved with reduced token usage and quicker streaming responses. Microsoft claims a 22% enhancement on Terminal-Bench 2.1 for GitHub Copilot CLI and a 15% boost in .NET task performance. Additionally, production outcomes indicate a 4% rise in code survival rates and a 9% increase in users returning to the platform. Notably, in GitHub Copilot, tokens are streamed 25% faster, and the model requires 25% fewer tokens for task completion, which translates to quicker responses, reduced wait times, and enhanced productivity from each token processed. These advancements stem from refined training methods and improved operational efficiencies, with a strong focus on practical application in real-world scenarios. Ultimately, MAI-Code-1.1-Flash represents a significant leap forward in coding assistance technology.

Description

Qwen 4 is the upcoming fourth-generation foundation model in Alibaba’s Qwen AI family. Alibaba publicly confirmed at its 2026 Apsara Conference that the model is currently being trained. The company has not yet released technical specifications, model weights, API access, pricing, benchmark results, or a launch date for Qwen 4. Its development forms part of Alibaba’s broader effort to advance foundation models capable of increasingly complex and long-horizon work. The Qwen team is also researching recursive self-improvement, in which models use empirical feedback to identify weaknesses, design experiments, evaluate results, and iteratively improve training processes. Alibaba demonstrated this approach with Qwen3.8-Max, which completed 33 automated optimization cycles during a month-long experiment and improved its Artificial Analysis score from 40 to 45. These experiments provide context for Alibaba’s model-development direction but do not establish specific Qwen 4 capabilities. Alibaba has additionally outlined Qwen 4.5 and Qwen 5 models that could eventually scale to between 5 trillion and 10 trillion parameters. Until Qwen 4 is released, its exact architecture, modalities, performance, deployment options, and licensing remain to be announced.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

No images available

Integrations

Alibaba Cloud No 
Cline No 
ClinePass No 
GitHub Copilot Yes 
Hermes Agent No 
Hugging Face No 
Microsoft Azure Yes 
Microsoft Foundry Yes 
Model Context Protocol (MCP) No 
ModelScope No 
Novita AI No 
Odysseus No 
OfoxAI No 
Ollama No 
Python No 
Qwen Code No 
Qwen Studio No 
QwenCloud No 
QwenWork No 
Visual Studio Code Yes 

Integrations

Alibaba Cloud Yes 
Cline Yes 
ClinePass Yes 
GitHub Copilot No 
Hermes Agent Yes 
Hugging Face Yes 
Microsoft Azure No 
Microsoft Foundry No 
Model Context Protocol (MCP) Yes 
ModelScope Yes 
Novita AI Yes 
Odysseus Yes 
OfoxAI Yes 
Ollama Yes 
Python Yes 
Qwen Code Yes 
Qwen Studio Yes 
QwenCloud Yes 
QwenWork Yes 
Visual Studio Code No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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

Microsoft AI

Founded

2024

Country

United States

Website

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

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai

Product Features

Alternatives

Alternatives

Qwen2 Reviews

Qwen2

Alibaba
Qwen3.8-27B Reviews

Qwen3.8-27B

Alibaba
MAI-Code-1-Flash Reviews

MAI-Code-1-Flash

Microsoft AI
Qwen3.6 Reviews

Qwen3.6

Alibaba
GPT-5.6 Sol Reviews

GPT-5.6 Sol

OpenAI