Meta Llama: Llama 3 8B Instruct
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Llama 3 8B Instruct is Meta's compact 8 billion parameter instruction-tuned model for dialogue use cases in English. It offers strong performance on common benchmarks while being more efficient to deploy than its larger sibling.
Context Window 8K
tokens
Max Output 8K
tokens
Input Cost $0.14
per million tokens
Output Cost $0.14
per million tokens
Release Date Apr 18, 2024
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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ChatLlama 4 Maverick
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Frequently Asked Questions
You can access Llama 3 8B 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.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Llama 3 8B 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.
| Price per 1M tokens | |
|---|---|
| Input | $0.14 |
| Output | $0.14 |
Llama 3 8B Instruct was created by Meta Llama and released on Apr 18, 2024.
Llama 3 8B Instruct supports a context window of 8K tokens. For reference, that is roughly equivalent to 16 pages of text.
Llama 3 8B Instruct can generate up to 8K tokens in a single response.
Llama 3 8B Instruct scores 1.0 on the Artificial Analysis Intelligence Index, outperforming 0% of tracked models.
Yes — the Llama 3 8B 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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