Meta Llama: Llama 3.1 8B
meta-llama/llama-3.1-8b
Access Llama 3.1 8B 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-3.1-8b"
}).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-3.1-8b"
}).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-3.1-8b",
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-3.1-8b",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Llama 3.1 8B is an 8-billion-parameter instruction-tuned chat model from Meta, released in July 2024 as the smallest member of the Llama 3.1 family.
It handles dialogue in eight languages (English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai) and was trained for tool use. Meta reports 73.0 on MMLU (0-shot, CoT), 84.5 on GSM8K, and 72.6 on HumanEval, a large improvement over Llama 3 8B's 60.4 on HumanEval, and positions it slightly ahead of Gemma 2 9B and Mistral 7B in its size class.
At a few cents per million tokens, it fits high-volume work such as chat assistants, summarization, classification, and translation, where a larger model's cost is not justified.
Context Window 33K
tokens
Max Output 8K
tokens
Input Cost $0.05
per million tokens
Output Cost $0.08
per million tokens
Tool Use Yes
Release Date Jul 23, 2024
Model Playground
Try Llama 3.1 8B instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
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ChatLlama 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.
ChatLlama 3.2 3B Instruct
Llama 3.2 3B Instruct is a compact 3 billion parameter model optimized for on-device use cases with 128K context support. It outperforms comparable models on instruction following, summarization, and tool-use tasks.
Frequently Asked Questions
You can access Llama 3.1 8B 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 3.1 8B 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 | $0.05 |
| Output | $0.08 |
Llama 3.1 8B was created by Meta Llama and released on Jul 23, 2024.
Llama 3.1 8B supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.
Llama 3.1 8B can generate up to 8K tokens in a single response.
Yes, Llama 3.1 8B supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the Llama 3.1 8B 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 8B to your app without worrying about API keys or setup.
Read the Docs View Tutorials