MAI-Code-1-Flash

MAI-Code-1-Flash

Microsoft AI
+
+

Related Products

  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • SOCRadar Extended Threat Intelligence
    115 Ratings
    Visit Website
  • Criminal IP
    457 Ratings
    Visit Website
  • ThreatLocker
    700 Ratings
    Visit Website
  • Daylight
    11 Ratings
    Visit Website
  • Rocket z/Assure VAP
    1 Rating
    Visit Website
  • LTX
    182 Ratings
    Visit Website
  • Bitdefender Ultimate Small Business Security
    5 Ratings
    Visit Website
  • Evertune
    1 Rating
    Visit Website
  • ESET PROTECT Advanced
    2,304 Ratings
    Visit Website

About

Gemini 3.5 Flash Cyber is a specialized cyber-focused model built on Gemini 3.5 Flash and fine-tuned to find, validate, and fix cybersecurity vulnerabilities efficiently at scale. It is designed for defensive security workflows where organizations need to identify critical weaknesses faster and generate reliable patches before those issues can be exploited. Flash’s combination of performance and efficiency makes it a strong foundation for scanning code, reasoning about security flaws, validating whether findings are real, and proposing targeted remediations across large software environments. Within CodeMender, multiple Gemini 3.5 Flash Cyber agents work together and combine their findings into a single report, helping the system investigate vulnerabilities from different angles and improve the quality of the final result. This coordinated agent setup delivers competitive frontier performance on CyberGym, a benchmark for evaluating cybersecurity capabilities.

About

MAI-Code-1-Flash is a Microsoft coding model built for fast, efficient assistance in everyday developer workflows. Built end-to-end by Microsoft using clean and appropriately licensed data, the model is rolling out to GitHub Copilot individual users in Visual Studio Code through the model picker and the default Auto picker. It is designed around the goal of delivering high-quality coding help with better efficiency, helping engineering teams write better code faster through a lightweight, agentic model integrated into GitHub Copilot and VS Code. MAI-Code-1-Flash was trained directly with GitHub Copilot production harnesses, allowing it to interact with surrounding tools and systems in real developer environments rather than being optimized only for static benchmarks. It supports agentic coding, strong instruction-following across single-turn and multi-turn scenarios, repository question answering, refactoring, telemetry-grounded tasks, and adaptive thinking.

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

Cybersecurity teams that need agentic tools to detect, validate, and patch critical software vulnerabilities

Audience

Developers and engineering teams that need a fast, efficient coding model for GitHub Copilot workflows, refactoring, repository Q&A, and agentic software engineering tasks

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

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

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

Reviews/Ratings

Overall 5.0 / 5
features 4.0 / 5

Pros & Cons from Real Users

Pros

  • What I like most is that it is not trying to be the biggest “solve everything” model. It is aimed at the work developers actually do all day: quick edits, explanations, refactors, small bug fixes, code cleanup, and iterative Copilot-style assistance. The GitHub Copilot and VS Code integration is the real advantage. A coding model becomes much more useful when it sits directly inside the editor instead of forcing me to bounce between tools. The efficiency angle matters too. Microsoft calls it a small-tier, inference-efficient coding model, and GitHub says it has been rolling out across more Copilot surfaces. For daily use, speed and cost can matter just as much as raw benchmark power.

Cons

  • The tradeoff is that I would not use it for every hard engineering problem. For deep architecture work, large multi-file changes, or tricky production bugs, I would still compare it against heavier reasoning models and review everything carefully.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Google
Founded: 1998
United States
gemini.google.com

Company Information

Microsoft AI
Founded: 2024
United States
microsoft.ai/news/introducingmai-code-1-flash/

Alternatives

Alternatives

GPT-5.6 Sol

GPT-5.6 Sol

OpenAI
Kimi K2.7 Code

Kimi K2.7 Code

Moonshot AI
MAI-Code-1.1-Flash

MAI-Code-1.1-Flash

Microsoft AI

Categories

Categories

Integrations

Android Studio
Bind AI
C
C++
Devin Desktop
Factory Droid
Gemini Enterprise
Gemini Enterprise Agent Platform Notebooks
Go
Google
Google AI Overviews
Google Antigravity
HTML
JetBrains Junie
Kubernetes
PHP
PowerShell
Replit
Visual Studio Code
YAML

Integrations

Android Studio
Bind AI
C
C++
Devin Desktop
Factory Droid
Gemini Enterprise
Gemini Enterprise Agent Platform Notebooks
Go
Google
Google AI Overviews
Google Antigravity
HTML
JetBrains Junie
Kubernetes
PHP
PowerShell
Replit
Visual Studio Code
YAML
Claim Gemini 3.5 Flash Cyber and update features and information
Claim Gemini 3.5 Flash Cyber and update features and information
Claim MAI-Code-1-Flash and update features and information
Claim MAI-Code-1-Flash and update features and information