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Description

Gemini 3.5 Flash-Lite stands out as the quickest model within Google's Gemini 3.5 lineup, specifically engineered for tasks requiring low latency and for enhancing developer workflows that demand high throughput, including agentic search, document processing, coding, and extensive data analysis. It boasts an impressive output capacity of 350 tokens per second and marks a significant enhancement over earlier Flash-Lite iterations in terms of both quality and agentic capabilities. Developers have the flexibility to adjust the model's thinking level to suit the demands of the task at hand: minimal or low thinking allows for rapid processing of large volumes, while elevated thinking levels accommodate more intricate, multi-step workflows involving subagents. Furthermore, the model is equipped with built-in computational skills, enabling it to interact effectively with various digital environments across compatible platforms. Additionally, Gemini 3.5 Flash-Lite excels in coding, comprehending long contexts, and executing real-world tasks, consistently outperforming its predecessor, Gemini 3.1 Flash-Lite, in critical assessments and even exceeding the performance of Gemini 3 Flash on multiple benchmarks related to agentic functions and software engineering. This impressive performance highlights its potential to transform how developers approach complex workflows and data-intensive tasks.

Description

MAI-Code-1-Flash is an innovative coding model developed by Microsoft, aimed at providing quick and effective support for developers in their daily tasks. This model, which has been meticulously created using clean and properly licensed data, is being introduced to GitHub Copilot individual users within Visual Studio Code via the model picker and the default Auto picker. Its primary objective is to enhance the quality of coding assistance while boosting efficiency, enabling engineering teams to produce superior code at a faster pace through a streamlined, agentic model seamlessly integrated into GitHub Copilot and VS Code. Notably, MAI-Code-1-Flash has been trained using GitHub Copilot production harnesses, equipping it to function in real developer settings and interact with various tools and systems rather than being solely fine-tuned for static benchmarks. The model excels in agentic coding, robust instruction-following across both single-turn and multi-turn interactions, answering questions related to repositories, performing refactoring, tackling telemetry-driven tasks, and showcasing adaptive thinking capabilities. In summary, this model represents a significant advancement in coding assistance technology, promising to transform how developers engage with their coding environments.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Android Studio Yes 
Bash Yes 
Cheaper Inference Yes 
Gemini 3.5 Flash Yes 
Gemini 3.5 Flash Cyber Yes 
Gemini 3.6 Flash Yes 
Gemini 3.7 Flash Yes 
Gemini Computer Use Yes 
Gemini Enterprise Yes 
Google Yes 
Google AI Ultra Yes 
HTML Yes 
Java Yes 
Kotlin Yes 
Kubernetes Yes 
OpenTag Yes 
Ruby Yes 
Scala Yes 
Swift Yes 
YAML Yes 

Integrations

Android Studio No 
Bash No 
Cheaper Inference No 
Gemini 3.5 Flash No 
Gemini 3.5 Flash Cyber No 
Gemini 3.6 Flash No 
Gemini 3.7 Flash No 
Gemini Computer Use No 
Gemini Enterprise No 
Google No 
Google AI Ultra No 
HTML No 
Java No 
Kotlin No 
Kubernetes No 
OpenTag No 
Ruby No 
Scala No 
Swift No 
YAML No 

Pricing Details

$0.30 per 1M input tokens
$0.30/1M input tokens and $2.50/1M output tokens
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

Google

Founded

1998

Country

United States

Website

gemini.google.com

Vendor Details

Company Name

Microsoft AI

Founded

2024

Country

United States

Website

microsoft.ai/news/introducingmai-code-1-flash/

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