Meta Llama: Llama 3.2 1B Instruct

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Llama 3.2 1B Instruct is Meta's ultra-lightweight 1 billion parameter model designed for edge and mobile devices. It supports 128K context and handles summarization, instruction following, and rewriting tasks locally.

Context Window 131K

tokens

Max Output 60K

tokens

Input Cost $0.03

per million tokens

Output Cost $0.2

per million tokens

Release Date Sep 25, 2024

 

Output Speed 92

tokens / sec

Latency 0.57s

time to first token

Code Example

Add AI to your app with the Puter.js AI API — no API keys or setup required.

// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms").then(response => {
    document.body.innerHTML = response.message.content;
});

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms").then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

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Frequently Asked Questions

How do I use Llama 3.2 1B Instruct?

You can access Llama 3.2 1B Instruct by Meta Llama through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.

Is Llama 3.2 1B Instruct free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Llama 3.2 1B Instruct to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.

What is the pricing for Llama 3.2 1B Instruct?
Llama 3.2 1B Instruct costs $0.03 per 1M input tokens and $0.2 per 1M output tokens.
Price per 1M tokens
Input$0.03
Output$0.2
Who created Llama 3.2 1B Instruct?

Llama 3.2 1B Instruct was created by Meta Llama and released on Sep 25, 2024.

What is the context window of Llama 3.2 1B Instruct?

Llama 3.2 1B Instruct supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.

What is the max output length of Llama 3.2 1B Instruct?

Llama 3.2 1B Instruct can generate up to 60K tokens in a single response.

How does Llama 3.2 1B Instruct perform on benchmarks?

Llama 3.2 1B Instruct scores 6.3 on the Artificial Analysis Intelligence Index, outperforming 1% of tracked models. On coding, it scores 0.6 (outperforms 1% of models). On math, it scores 0.0 (outperforms 0% of models).

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Llama 3.2 1B Instruct API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

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