`puter.ai.txt2img()`

Given a prompt, generate an image using AI.

Syntax

puter.ai.txt2img(prompt, testMode = false)
puter.ai.txt2img(prompt, options = {})

Parameters

`prompt` (String) (required)

A string containing the prompt you want to generate an image from.

`testMode` (Boolean) (Optional)

A boolean indicating whether you want to use the test API. Defaults to false. This is useful for testing your code without using up API credits.

`options` (Object) (Optional)

An options object with the following properties:

model (String) (Optional) - The AI model to use for image generation, it can be gpt-image-1, gemini-2.5-flash-image-preview (also known as Nano Banana), or dall-e-3. Defaults to gpt-image-1.
quality (String) (Optional) - The quality of the generated image. For gpt-image-1, it can be high, medium or low. Defaults to low. There is no quality setting for gemini-2.5-flash-image-preview. For dall-e-3, it can be hd or standard. Defaults to standard.
input_image (String) (Optional) (Only works with gemini-2.5-flash-image-preview) - Base64 encoded input image for image-to-image generation.
input_image_mime_type (String) (Optional) (Only if input_image is set) - The MIME type of the input image. Could be image/png, image/jpeg, image/jpg, or image/webp.

Return value

A Promise that will resolve to an image data URL when the image has been generated.

Examples

Generate an image of a cat using AI

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        // Generate an image of a cat using the default model and quality. Please note that testMode is set to true so that you can test this code without using up API credits.
        puter.ai.txt2img('A picture of a cat.', true).then((image)=>{
            document.body.appendChild(image);
        });
    </script>
</body>
</html>

Generate an image with specific model and quality

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        // Generate am image of a cat playing piano using a specific model and quality set to low
        puter.ai.txt2img("a cat playing piano", { 
            model: "gpt-image-1", 
            quality: "low" 
        }).then((image)=>{
            document.body.appendChild(image);
        });
    </script>
</body>
</html>

Generate an image with image-to-image generation

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.txt2img("a cat playing piano", { 
            model: "gemini-2.5-flash-image-preview",
            input_image: "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",
            input_image_mime_type: "image/png"
        }).then((image)=>{
            document.body.appendChild(image);
        });
    </script>
</body>
</html>

img2txt()

chat()

puter.ai.txt2img()