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FREE UNLIMITED OpenAI

A tutorial of how to get free unlimited OpenAI API

This tutorial will show you how to use Puter.js to access OpenAI API capabilities for free, without needing an OpenAI API key. Puter.js is completely free and open-source, allowing you to provide your users with powerful AI capabilities without any API keys or usage restrictions. Using Puter.js, you can access GPT-4o, GPT-4.1, GPT-4.5, o1, o3, o4, DALL-E, ... directly from your frontend code without any server-side setup.

Getting Started
You can use puter.js without any API keys or sign-ups. To start using Puter.js, include the following script tag in your HTML file, either in the or section:

<script src="https://js.puter.com/v2/"></script>


Nothing else is required to start using Puter.js for free access to OpenAI API models and capabilities.

Example 1
Use GPT-4o for text generation
To generate text using GPT-4o, use the puter.ai.chat() function:

puter.ai.chat("What are the benefits of exercise?")
    .then(response => {
        puter.print(response);
    });

Full code example:

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("What are the benefits of exercise?")
            .then(response => {
                puter.print(response);
            });
    </script>
</body>
</html>

Example 2
Generate images with DALL-E 3
To create images using DALL-E 3, use the puter.ai.txt2img() function:

puter.ai.txt2img("A futuristic cityscape at night")
    .then(imageElement => {
        document.body.appendChild(imageElement);
    });

Full code example:

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.txt2img("A futuristic cityscape at night")
            .then(imageElement => {
                document.body.appendChild(imageElement);
            });
    </script>
</body>
</html>

Example 3
Analyze images with GPT-4o Vision To analyze images using GPT-4o Vision, provide an image URL to puter.ai.chat():

puter.ai.chat(
    "What do you see in this image?", 
    "https://assets.puter.site/doge.jpeg"
)
.then(response => {
    puter.print(response);
});

Full code example:

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat(
            "What do you see in this image?", 
            "https://assets.puter.site/doge.jpeg"
        )
        .then(response => {
            puter.print(response);
        });
    </script>
</body>
</html>

Example 4
Use different OpenAI models
You can specify different OpenAI models using the model parameter, for example gpt-4.1, o3-mini, o1-mini, or gpt-4o:

// Using gpt-4.1 model
puter.ai.chat(
    "Write a short poem about coding",
    { model: "gpt-4.1" }
).then(response => {
    puter.print(response);
});

// Using o3-mini model
puter.ai.chat(
    "Write a short poem about coding",
    { model: "o3-mini" }
).then(response => {
    puter.print(response);
});

// Using o1-mini model
puter.ai.chat(
    "Write a short poem about coding",
    { model: "o1-mini" }
).then(response => {
    puter.print(response);
});

// Using 4o model
puter.ai.chat(
    "Write a short poem about coding",
    { model: "gpt-4o" }
).then(response => {
    puter.print(response);
});

Full code example:

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        // Using gpt-4.1 model
        puter.ai.chat(
            "Write a short poem about coding",
            { model: "gpt-4.1" }
        ).then(response => {
            puter.print("<h2>Using gpt-4.1 model</h2>");
            puter.print(response);
        });

        // Using o3-mini model
        puter.ai.chat(
            "Write a short poem about coding",
            { model: "o3-mini" }
        ).then(response => {
            puter.print("<h2>Using o3-mini model</h2>");
            puter.print(response);
        });

        // Using o1-mini model
        puter.ai.chat(
            "Write a short poem about coding",
            { model: "o1-mini" }
        ).then(response => {
            puter.print("<h2>Using o1-mini model</h2>");
            puter.print(response);
        });

        // Using 4o model
        puter.ai.chat(
            "Write a short poem about coding",
            { model: "gpt-4o" }
        ).then(response => {
            puter.print("<h2>Using gpt-4o model</h2>");
            puter.print(response);
        });
    </script>
</body>
</html>

Example 5
Stream responses for longer queries For longer responses, use streaming to get results in real-time:

async function streamResponse() {
    const response = await puter.ai.chat(
        "Explain the theory of relativity in detail", 
        {stream: true}
    );
    
    for await (const part of response) {
        puter.print(part?.text);
    }
}

streamResponse();

Full code example:

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        async function streamResponse() {
            const response = await puter.ai.chat(
                "Explain the theory of relativity in detail", 
                {stream: true}
            );
            
            for await (const part of response) {
                puter.print(part?.text);
            }
        }

        streamResponse();
    </script>
</body>
</html>

List of supported models The following OpenAI models are supported by Puter.js:

gpt-4.1
gpt-4.1-mini
gpt-4.1-nano
gpt-4.5-preview
gpt-4o
gpt-4o-mini
o1
o1-mini
o1-pro
o3
o3-mini
o4-mini

That's it! You now have a free alternative to the OpenAI API using Puter.js. This allows you to access GPT-4o, o4, o3-mini, o1-mini, DALL-E, ... capabilities without needing an API key or a backend. True serverless AI!

If you found this helpful or want to use it in your project please star this repo! Happy Coding!

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