Developers & Practitioners

Introducing Google Gen AI .NET SDK

October 23, 2025

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Mete Atamel

Cloud Developer Advocate

Last year, we announced the Google Gen AI SDK as the new unified library for Gemini on Google AI (via the Gemini Developer API ) and Vertex AI (via the Vertex AI API ). At the time, it was only a Python SDK. Since then, the team has been busy adding support for Go , Node.js , and Java but my favorite language, C# , was missing until now.

Today, I’m happy to announce that we now have a Google Gen AI .NET SDK ! This SDK enables C#/.NET developers use Gemini from Google AI or Vertex AI with a single unified library.

Let’s take a look at the details.

Installation

To install the library, run the following command in your .NET project directory:

Import it to your code as follows:

Create a client

First, you need to create a client to talk to Gemini.

You can target Gemini on Google AI (via the Gemini Developer API ):

Or you can target Gemini on Vertex AI (via the Vertex AI API ):

Generate text

Once you have the client, you can generate text with a unary response:

You can also generate text with a streaming response:

Generate image

Generating images is also straightforward with the new library:

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Configuration

Of course, all of the text and image generation is highly configurable.

For example, you can define a response schema and a generation configuration with system instructions and other settings for text generation as follows:

// Define a response schema
Schema countryInfo = new()
{
    Properties = new Dictionary<string, Schema> {
          {
            "name", new Schema { Type = Type.STRING, Title = "Name" }
          },
          {
            "population", new Schema { Type = Type.INTEGER, Title = "Population" }
          },
          {
            "capital", new Schema { Type = Type.STRING, Title = "Capital" }
          },
          {
            "language", new Schema { Type = Type.STRING, Title = "Language" }
          }
    },
    PropertyOrdering = ["name", "population", "capital", "language"],
    Required = ["name", "population", "capital", "language"],
    Title = "CountryInfo",
    Type = Type.OBJECT
};

// Define a generation config
GenerateContentConfig config = new()
{
    ResponseSchema = countryInfo,
    ResponseMimeType = "application/json",
    SystemInstruction = new Content
    {
        Parts = [
              new Part {Text = "Only answer questions on countries. For everything else, say I don't know."}
        ]
    },
    MaxOutputTokens = 1024,
    Temperature = 0.1,
    TopP = 0.8,
    TopK = 40,
};

var response = await client.Models.GenerateContentAsync(
     model: "gemini-2.5-flash",
     contents: "Give me information about Cyprus",
     config: config);

Similarly, you can specify image generation configuration: