MAI-Code-1-Flash

MAI-Code-1-Flash

Microsoft AI
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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.

About

Mistral Medium 3.5 is a flagship 128B dense model that merges instruction-following, reasoning, and coding into a single set of weights. It has a 256K context window, configurable reasoning effort, multimodal input, strong agentic capabilities, and is built for long-horizon tasks that require reliable multi-tool use and structured outputs. The model powers remote agents in Mistral Vibe, allowing coding sessions to run in the cloud, work through long tasks independently, and execute multiple sessions in parallel. Agents can be launched from the Vibe CLI or Le Chat, with local CLI sessions moved to the cloud while preserving history, task state, and approvals. Users can inspect file diffs, tool calls, progress states, and questions as work proceeds. Each coding session runs in an isolated sandbox and can handle module refactors, test generation, dependency upgrades, CI investigations, and bug fixes, then open a GitHub pull request for review.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook Not Supported

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

Audience

Developers, engineering teams, and knowledge workers seeking to delegate coding, research, and cross-tool workflows to autonomous cloud-based AI agents

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

$14.99 per month
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5
features 4.0 / 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:

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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 Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

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

Company Information

Mistral AI
Founded: 2023
France
mistral.ai/news/vibe-remote-agents-mistral-medium-3-5/

Alternatives

Alternatives

Mistral Vibe

Mistral Vibe

Mistral AI
Mistral Small 4

Mistral Small 4

Mistral AI
Kimi K2.7 Code

Kimi K2.7 Code

Moonshot AI
MAI-Code-1.1-Flash

MAI-Code-1.1-Flash

Microsoft AI
GLM-5.1

GLM-5.1

Z.ai
Mistral Large

Mistral Large

Mistral AI

Categories

AI Coding Models Supported
AI Models Supported

Categories

AI Models Supported

Integrations

GitHub Not Supported
GitHub Copilot Supported
Jira Not Supported
Linear Not Supported
Microsoft Azure Supported
Microsoft Foundry Supported
Microsoft Teams Not Supported
Sentry Not Supported
Slack Not Supported
Visual Studio Code Supported

Integrations

GitHub Supported
GitHub Copilot Not Supported
Jira Supported
Linear Supported
Microsoft Azure Not Supported
Microsoft Foundry Not Supported
Microsoft Teams Supported
Sentry Supported
Slack Supported
Visual Studio Code Not Supported
Claim MAI-Code-1-Flash and update features and information
Claim MAI-Code-1-Flash and update features and information
Claim Mistral Medium 3.5 and update features and information
Claim Mistral Medium 3.5 and update features and information