MAI-Code-1-Flash

MAI-Code-1-Flash

Microsoft AI
+
+

Related Products

  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • Google AI Studio
    30 Ratings
    Visit Website
  • Google Workspace
    69,107 Ratings
    Visit Website
  • Google Cloud BigQuery
    2,023 Ratings
    Visit Website
  • Evertune
    1 Rating
    Visit Website
  • Gemini Credit Card
    2 Ratings
    Visit Website
  • AthenaHQ
    36 Ratings
    Visit Website
  • AuthorityTech
    2 Ratings
    Visit Website
  • LM-Kit.NET
    29 Ratings
    Visit Website
  • HubSpot AEO
    47 Ratings
    Visit Website

About

Gemini 3.6 Flash is Google’s newest Flash model built for efficient, reliable, production-scale AI agents. The model improves on Gemini 3.5 Flash with stronger coding, knowledge work, multimodal performance, computer use, and agentic workflow execution. Gemini 3.6 Flash is designed to use fewer output tokens, take fewer reasoning steps, reduce unnecessary tool calls, and lower the cost of complex AI tasks. It supports document parsing, chart analysis, data analysis, report drafting, code migrations, visual understanding, and multi-agent orchestration. The model is available through the Gemini API, Google AI Studio, Android Studio, Google Antigravity, Gemini Enterprise Agent Platform, Gemini Enterprise app, and the Gemini app. Built for developers and enterprises, Gemini 3.6 Flash helps teams build faster, lower-cost, and more capable AI agents across coding, analysis, productivity, and multimodal workloads.

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

Developers, AI agent builders, enterprise AI teams, software engineering teams, data analysts, knowledge workers, product teams, and organizations that need efficient coding support, multimodal reasoning, computer use, document analysis, agentic workflows, lower token usage, and production-scale Gemini API access

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

$1.50 per 1M tokens (input)
$1.50/1M input tokens and $7.50/1M output tokens
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5
ease 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

  • Gemini 3.6 Flash feels like a really solid upgrade from a developer’s point of view. I like that Google is not just chasing “bigger model” headlines here, but focusing on the stuff that matters when you are actually building: coding quality, speed, cost, and token efficiency. The 17% fewer output tokens claim is a big deal for developers running agents, coding assistants, or high-volume workflows. When a model is being called over and over for planning, code edits, summaries, tool calls, and debugging loops, small efficiency gains can turn into real savings.

Cons

  • The main downside is that Flash still sounds like the efficient model, not the absolute top-end reasoning model. For really hard architecture work, long autonomous coding runs, or deep research-heavy tasks, I would still want to test it against the strongest frontier models before making it my default.

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

Claude Opus 5

Claude Opus 5

Anthropic

Alternatives

Claude Fable 5

Claude Fable 5

Anthropic
Claude Mythos 5

Claude Mythos 5

Anthropic
Kimi K2.7 Code

Kimi K2.7 Code

Moonshot AI
Gemini 4

Gemini 4

Google
StarCoder

StarCoder

BigCode

Categories

Categories

Integrations

.NET
Bash
Bind AI
C++
CSS
Gemini 3.5 Flash
Gemini Enterprise
Gemini Managed Agents
Google
Google AI Plus
Google AI Ultra
Google Antigravity
HTML
Java
OfoxAI
PowerShell
R
Replit
Visual Studio Code
XML

Integrations

.NET
Bash
Bind AI
C++
CSS
Gemini 3.5 Flash
Gemini Enterprise
Gemini Managed Agents
Google
Google AI Plus
Google AI Ultra
Google Antigravity
HTML
Java
OfoxAI
PowerShell
R
Replit
Visual Studio Code
XML
Claim Gemini 3.6 Flash and update features and information
Claim Gemini 3.6 Flash 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