---
title: Meta: Llama 3.1 8B Instruct — Multilingual LLM | ModelsLab
description: Access Meta: Llama 3.1 8B Instruct API for 128K context multilingual dialogue and instruction tasks. Generate responses via simple endpoints now.
url: https://modelslab.com/meta-llama-31-8b-instruct
canonical: https://modelslab.com/meta-llama-31-8b-instruct
type: website
component: Seo/ModelPage
generated_at: 2026-04-15T00:25:50.713291Z
---

Available now on ModelsLab · Language Model

Meta: Llama 3.1 8B Instruct
Compact Multilingual Power
---

[Try Meta: Llama 3.1 8B Instruct](/models/open_router/meta-llama-llama-3.1-8b-instruct) [API Documentation](https://docs.modelslab.com)

Deploy Llama 3.1 Efficiently
---

128K Context

### Process Long Inputs

Handle 128,000 tokens for extended documents and conversations in Meta: Llama 3.1 8B Instruct model.

Multilingual Dialogue

### Optimized Conversations

Supports eight languages for chatbots and agents using Meta: Llama 3.1 8B Instruct API.

Edge Deployment

### Resource Efficient

8B parameters suit constrained environments as Meta: Llama 3.1 8B Instruct alternative.

Examples

See what Meta: Llama 3.1 8B Instruct can create
---

Copy any prompt below and try it yourself in the [playground](/models/open_router/meta-llama-llama-3.1-8b-instruct).

Code Assistant

“You are a senior Python developer. Write a function to parse JSON logs, extract error timestamps, and summarize failures by type. Include error handling and unit tests.”

Text Summarizer

“Summarize this 5000-word technical report on renewable energy trends: \[insert long report text\]. Focus on key statistics, regional differences, and future projections in bullet points.”

Multilingual Q&A

“Respond in Spanish to: 'Explica los beneficios de la inteligencia artificial en la agricultura moderna, con ejemplos específicos de optimización de cultivos.' Keep response under 200 words.”

Instruction Follower

“Create a detailed project plan for building a web app: steps, tech stack (React, Node.js), timeline for 4 weeks, and risk mitigation. Format as markdown with tables.”

For Developers

A few lines of code.
Instruct Llama. One Call.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about Meta: Llama 3.1 8B Instruct
---

[Read the docs ](https://docs.modelslab.com)

### What is Meta: Llama 3.1 8B Instruct model?

### How to use Meta: Llama 3.1 8B Instruct API?

### What context length for meta llama 3.1 8b instruct?

### Is Meta: Llama 3.1 8B Instruct good for edge devices?

### Best Meta: Llama 3.1 8B Instruct alternative?

### Does meta: llama 3.1 8b instruct api support tools?

Ready to create?
---

Start generating with Meta: Llama 3.1 8B Instruct on ModelsLab.

[Try Meta: Llama 3.1 8B Instruct](/models/open_router/meta-llama-llama-3.1-8b-instruct) [API Documentation](https://docs.modelslab.com)

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*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

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*Generated by ModelsLab - 2026-04-15*