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Meta Llama: Meta Llama 3 8B Instruct Lite

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Meta Llama 3 8B Instruct Lite is a cost-optimized serving tier for Meta's Llama 3 8B Instruct, an 8-billion-parameter open-weight chat model pretrained on over 15 trillion tokens.

Despite its small size, it delivers strong reasoning, coding, and general-purpose conversation. On published benchmarks it scores around 67.4 on MMLU, 79.6% on GSM8K math, and 62.2% on HumanEval coding, making it highly competitive among models in its tier.

The Lite tier offers the same quality at a lower per-token price, making it a great fit for developers who need fast, affordable responses for chat assistants, summarization, classification, and lightweight coding tasks at scale.

Context Window 8K

tokens

Max Output 8K

tokens

Input Cost $0.14

per million tokens

Output Cost $0.14

per million tokens

Input text

modalities

Knowledge Cutoff Mar 2023

 

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>

More AI Models From Meta Llama

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Muse Glimmer 30B is a 30-billion-parameter dense model from Meta Superintelligence Labs, pairing a causal transformer with a 1.8-billion-parameter vision encoder for text and image input. It's released under an Apache 2.0 license, Meta's first fully open-weight model since Muse Spark moved to a paid API. On Meta's own benchmarks, it scores 76.0 on SWE-Bench Verified, 51.2 on SWE-Bench Pro, 94.7 on AIME 2026, 83.5 on GPQA Diamond, 75.5 on MCP Atlas, and 74.6 on DeepSearch QA, ahead of similarly sized open models like Gemma4 31B and Qwen3.6 27B on Meta's reporting. These figures are vendor-reported and not independently verified. Where Muse Spark targets large-scale multi-agent orchestration, Muse Glimmer sits a size tier down, aimed at tool use, multi-step reasoning, coding, and LLM-as-a-judge evaluation with a 131,072-token context window. It fits developers who want agentic and coding capability at lower cost than the larger Muse Spark models.

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Muse Spark 1.1

Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs, built for agentic workflows. It accepts text, images, video, audio, and PDF documents as input and returns text, with a 1,048,576-token context window. The model is designed to orchestrate multi-agent workflows, acting as either a main agent that plans and delegates tasks or as a subagent, and it generalizes zero-shot to new tools, MCP servers, and custom skills. It supports parallel function calling, structured output, built-in search with citations, and configurable reasoning effort, and Meta reports strong results on coding across large codebases, computer-use tasks, and visual-to-code generation. This is Meta's first model available through a paid API, priced at $1.25 per million input tokens and $4.25 per million output tokens, aimed at developers building agentic coding tools and enterprise workflow automation.

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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.

Frequently Asked Questions

How do I use Meta Llama 3 8B Instruct Lite?

You can access Meta Llama 3 8B Instruct Lite 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 Meta Llama 3 8B Instruct Lite free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Meta Llama 3 8B Instruct Lite 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 Meta Llama 3 8B Instruct Lite?
Meta Llama 3 8B Instruct Lite 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 Meta Llama 3 8B Instruct Lite?

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

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

Meta Llama 3 8B Instruct Lite 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 Meta Llama 3 8B Instruct Lite?

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

What is the knowledge cutoff of Meta Llama 3 8B Instruct Lite?

Meta Llama 3 8B Instruct Lite has a knowledge cutoff date of Mar 2023. This means the model was trained on data available up to that date.

What types of input can Meta Llama 3 8B Instruct Lite process?

Meta Llama 3 8B Instruct Lite accepts the following input types: text. It produces: text.

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

Yes — the Meta Llama 3 8B Instruct Lite 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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