Meta Llama

Meta Llama: Llama 3.1 70B Instruct

meta-llama/llama-3.1-70b-instruct

Access Llama 3.1 70B Instruct from Meta Llama using Puter.js AI API.

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

puter.ai.chat("Explain quantum computing in simple terms", {
    model: "meta-llama/llama-3.1-70b-instruct"
}).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", {
            model: "meta-llama/llama-3.1-70b-instruct"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

# pip install openai
from openai import OpenAI

client = OpenAI(
    base_url="https://api.puter.com/puterai/openai/v1/",
    api_key="YOUR_PUTER_AUTH_TOKEN",
)

response = client.chat.completions.create(
    model="meta-llama/llama-3.1-70b-instruct",
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms"}
    ],
)

print(response.choices[0].message.content)

curl https://api.puter.com/puterai/openai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
  -d '{
    "model": "meta-llama/llama-3.1-70b-instruct",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Model Card

Llama 3.1 70B Instruct is a multilingual 70 billion parameter model with 128K context length, optimized for dialogue, tool use, and coding tasks. It balances strong performance with resource efficiency across 8 supported languages.

Context Window 131K

tokens

Max Output N/A

tokens

Input Cost $0.4

per million tokens

Output Cost $0.4

per million tokens

Release Date Jul 23, 2024

 

Output Speed 31

tokens / sec

Latency 0.77s

time to first token

Model Playground

Try Llama 3.1 70B Instruct instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat meta-llama/llama-3.1-70b-instruct
Meta Llama
Chat with Llama 3.1 70B Instruct
Powered by Puter.js

Benchmarks

How Llama 3.1 70B Instruct performs on standard evaluations.

Artificial Analysis
Intelligence Index
12.5
Better than 25% of tracked models
Artificial Analysis
Coding Index
10.9
Better than 26% of tracked models
Artificial Analysis
Math Index
4.0
Better than 6% of tracked models
BenchmarkScore
GPQA Diamond Graduate-level science Q&A
40.9%
Humanity's Last Exam Cross-domain reasoning
4.6%
LiveCodeBench Recent coding problems
23.2%
SciCode Scientific programming
26.7%
MATH-500 Competition math
64.9%
AIME 2024 Advanced math exam
17.3%
AIME 2025 Advanced math exam
4.0%
IFBench Instruction following
34.4%
LCR Long-context reasoning
6.3%
Terminal-Bench Hard Agentic terminal tasks
3.0%
τ²-Bench Tool use / agents
15.2%

Scores sourced from Artificial Analysis.

Find other Meta Llama models →

Chat

Llama Guard 4 12B

Llama Guard 4 12B is Meta's 12 billion parameter multimodal safety model that moderates both text and image inputs across 12 languages. It was built from Llama 4 Scout and detects violations based on the MLCommons hazard taxonomy.

 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.

Frequently Asked Questions

How do I use Llama 3.1 70B Instruct?

You can access Llama 3.1 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 3.1 70B Instruct free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Llama 3.1 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 3.1 70B Instruct?
Pricing for Llama 3.1 70B Instruct is based on the number of input and output tokens used per request.
Price per 1M tokens
Input$0.4
Output$0.4
Who created Llama 3.1 70B Instruct?

Llama 3.1 70B Instruct was created by Meta Llama and released on Jul 23, 2024.

What is the context window of Llama 3.1 70B Instruct?

Llama 3.1 70B Instruct supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.

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

Yes — the Llama 3.1 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 Llama 3.1 70B Instruct to your app without worrying about API keys or setup.

Read the Docs View Tutorials