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Meta Llama: Llama 3 8B Instruct

This model is no longer available.

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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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Muse Spark Open

Muse Spark Open is an open-weight multimodal model from Meta, released on October 15, 2026. It is a mixture-of-experts model with 816B total and 42B active parameters and a 1,048,576-token context window. It accepts text, image, video, and audio input and returns text. It is aimed at agentic and tool-use work. Meta reports that it leads the open models it compared against on the agentic benchmarks MCP-Atlas and JobBench, and that it trails some closed Chinese models such as Kimi K3 and GLM 5.3 on the coding benchmark Terminal-Bench 2.1. These results are vendor-reported. It supports tool calling, structured output, and configurable reasoning effort. It suits developers who want an agent-capable model with open weights from a US lab.

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Muse Wonder

Muse Wonder is a multimodal agent model from Meta Superintelligence Labs, built on Muse Spark and released on October 12, 2026. It accepts text, images, video, audio, and PDF input, returns text, and has a 1,048,576-token context window. It is designed for long, multi-step agent work such as coding, legal and financial documents, and tasks across several apps. It supports tool calling, structured output, and configurable reasoning effort. Meta reports 78.8 on DeepSWE 1.1 and 53.1 on SWE-Marathon, and Artificial Analysis gives it an Intelligence Index score of 52, up from 48 for Muse Spark 1.3. Its per-token price is below Claude Fable 5.1 ($10 input, $50 output), though Claude Opus 5.5 scores higher on the index and on OSWorld.

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Muse Spark 1.3

Muse Spark 1.3 is Meta Superintelligence Labs' follow-up to the coding-focused Muse Spark 1.2, released on September 2, 2026. It targets long-horizon agentic work, multi-agent orchestration, and extended multi-step coding tasks. On Meta's own harness it scored 88.8% on Terminal-Bench 2.1, level with OpenAI's GPT-5.6 Sol, and 75.4% on DeepSWE 1.1, up from 59.3% for 1.2. These are vendor-reported numbers, not yet independently verified. Artificial Analysis gives it an Intelligence Index score of 48, up from 40 for Muse Spark 1.2, and Anthropic's Opus 5 still leads it on several agent benchmarks. It keeps the 1,048,576-token context window, text, image, video, and PDF input, and tool calling from earlier versions, at the same $1.25 per million input and $4.25 per million output token pricing.

Frequently Asked Questions

How do I use Llama 3 8B Instruct?

Llama 3 8B Instruct is no longer available through Puter.js. Explore other AI models for alternatives.

What is the pricing for Llama 3 8B Instruct?
Llama 3 8B Instruct costs $0.14 per 1M input tokens and $0.14 per 1M output tokens.
Price per 1M tokens
Input$0.14
Output$0.14
Who created Llama 3 8B Instruct?

Llama 3 8B Instruct was created by Meta Llama and released on Apr 18, 2024.

What is the context window of Llama 3 8B Instruct?

Llama 3 8B Instruct supports a context window of 8K tokens. For reference, that is roughly equivalent to 16 pages of text.

What is the max output length of Llama 3 8B Instruct?

Llama 3 8B Instruct can generate up to 8K tokens in a single response.

How does Llama 3 8B Instruct perform on benchmarks?

Llama 3 8B Instruct scores 4.8 on the Artificial Analysis Intelligence Index, outperforming 0% of tracked models.

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

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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