Meta Llama: Llama 3.3 70B Instruct

This model is no longer available.

Add AI to your application with Puter.js.

Explore Other Models

Model Card

Llama 3.3 70B Instruct is Meta's refined 70 billion parameter multilingual model with improved instruction following and tool use capabilities. It supports 8 languages and offers enhanced reasoning performance over previous versions.

Context Window 131K

tokens

Max Output 16K

tokens

Input Cost $0.1

per million tokens

Output Cost $0.32

per million tokens

Release Date Dec 6, 2024

 

Output Speed 92

tokens / sec

Latency 0.64s

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>

More AI Models From Meta Llama

Find other Meta Llama models →

Chat

Llama 4 Maverick

Llama 4 Maverick is Meta's 400 billion total parameter MoE model with 17B active parameters and 128 experts, supporting 1M token context. It's natively multimodal with state-of-the-art performance on coding, reasoning, and image understanding tasks.

 Chat

Llama 4 Scout

Llama 4 Scout is Meta's efficient 109 billion parameter MoE model with 17B active parameters and 16 experts, featuring an industry-leading 10M token context window. It fits on a single H100 GPU and handles multimodal text and image inputs.

 Chat

Llama Guard 3 8B

Llama Guard 3 8B is Meta's enhanced safety moderation model providing content classification in 8 languages with support for tool call safety. It detects 14 hazard categories and integrates with Llama 3.1 for comprehensive AI safety.

Frequently Asked Questions

How do I use Llama 3.3 70B Instruct?

You can access Llama 3.3 70B 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 3.3 70B Instruct free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Llama 3.3 70B 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 3.3 70B Instruct?
Llama 3.3 70B Instruct costs $0.1 per 1M input tokens and $0.32 per 1M output tokens.
Price per 1M tokens
Input$0.1
Output$0.32
Who created Llama 3.3 70B Instruct?

Llama 3.3 70B Instruct was created by Meta Llama and released on Dec 6, 2024.

What is the context window of Llama 3.3 70B Instruct?

Llama 3.3 70B 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 3.3 70B Instruct?

Llama 3.3 70B Instruct can generate up to 16K tokens in a single response.

How does Llama 3.3 70B Instruct perform on benchmarks?

Llama 3.3 70B Instruct scores 14.5 on the Artificial Analysis Intelligence Index, outperforming 32% of tracked models. On coding, it scores 10.7 (outperforms 24% of models). On math, it scores 7.7 (outperforms 11% of models).

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

Yes — the Llama 3.3 70B 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.

Get started with Puter.js

Add AI to your application without worrying about API keys or setup.

Explore Models View Tutorials