XLarge Models (40B+ Parameters)

Our XLarge models, featuring Llama-3.1-70B, represent the most powerful language models in our lineup. With over 40 billion parameters, these models excel at complex reasoning, nuanced understanding, and sophisticated content generation.

Available Models

Llama-3.1-70B

• Parameters: 70B
• Context Window: 128,000 tokens
• Provider: Meta
• License: Meta Llama 3 License
• Key Features:
  • Multilingual capabilities
  • Advanced reasoning
  • Complex task handling
  • Long context understanding

Configuration & Setup

OpenAI SDK

import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: 'your-neuredge-key',
  baseURL: 'https://api.neuredge.dev/v1/'
});

Native SDK

import { Neuredge } from '@neuredge/sdk';

const neuredge = new Neuredge({
  apiKey: 'your-api-key'
});

Real-World Applications & Examples

1. Advanced Content Creation

Blog Post Generation

const response = await openai.chat.completions.create({
  model: '@cf/meta/llama-3.1-70b-instruct',
  messages: [
    {
      role: 'system',
      content: 'You are an expert content writer specializing in technical topics. Write in a clear, engaging style with concrete examples.'
    },
    {
      role: 'user',
      content: 'Write a comprehensive blog post about the impact of AI on healthcare, focusing on recent developments and future prospects.'
    }
  ],
  temperature: 0.7,
  max_tokens: 1000
});

Use Cases:

• Long-form content creation
• Technical documentation
• Research paper drafting
• Marketing copy with industry expertise
• Educational content development

2. Enterprise Document Analysis

Contract Review Assistant

const response = await openai.chat.completions.create({
  model: '@cf/meta/llama-3.1-70b-instruct',
  messages: [
    {
      role: 'system',
      content: 'You are a legal document analyst. Review contracts for potential issues and summarize key points.'
    },
    {
      role: 'user',
      content: \`Review this contract clause:
      ${contractText}
      Identify potential risks and suggest improvements.\`
    }
  ],
  temperature: 0.3
});

Use Cases:

• Legal document review
• Compliance checking
• Policy analysis
• Risk assessment
• Contract summarization

3. Research & Analysis

Literature Review

const response = await openai.chat.completions.create({
  model: '@cf/meta/llama-3.1-70b-instruct',
  messages: [
    {
      role: 'system',
      content: 'You are a research assistant helping with academic literature review. Analyze papers and identify key findings and methodologies.'
    },
    {
      role: 'user',
      content: \`Analyze these research abstracts and identify common themes and contradictions:
      ${abstracts.join('\n\n')}\`
    }
  ],
  temperature: 0.2,
  max_tokens: 1500
});

Use Cases:

• Academic research
• Meta-analysis
• Systematic reviews
• Research synthesis
• Methodology comparison

4. Complex Problem Solving

System Architecture Design

const response = await openai.chat.completions.create({
  model: '@cf/meta/llama-3.1-70b-instruct',
  messages: [
    {
      role: 'system',
      content: 'You are a solutions architect helping design scalable systems.'
    },
    {
      role: 'user',
      content: \`Design a microservices architecture for an e-commerce platform that needs to handle:
      - 1M daily active users
      - Real-time inventory
      - Payment processing
      - Order fulfillment
      Provide detailed component breakdown and communication patterns.\`
    }
  ],
  temperature: 0.4
});

Use Cases:

• System design
• Architecture planning
• Technical solution design
• Performance optimization strategies
• Scalability planning

Integration Examples

Express.js REST API

import express from 'express';
import OpenAI from 'openai';

const app = express();
app.use(express.json());

const openai = new OpenAI({
  apiKey: process.env.NEUREDGE_API_KEY,
  baseURL: 'https://api.neuredge.dev/v1/'
});

app.post('/analyze', async (req, res) => {
  try {
    const { text } = req.body;
    const response = await openai.chat.completions.create({
      model: '@cf/meta/llama-3.1-70b-instruct',
      messages: [
        {
          role: 'system',
          content: 'Analyze the following text and provide key insights.'
        },
        {
          role: 'user',
          content: text
        }
      ]
    });
    
    res.json({ analysis: response.choices[0].message.content });
  } catch (error) {
    res.status(500).json({ error: error.message });
  }
});

Next.js API Route

// pages/api/generate.js
import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: process.env.NEUREDGE_API_KEY,
  baseURL: 'https://api.neuredge.dev/v1/'
});

export default async function handler(req, res) {
  if (req.method !== 'POST') {
    return res.status(405).json({ message: 'Method not allowed' });
  }

  try {
    const { prompt } = req.body;
    const response = await openai.chat.completions.create({
      model: '@cf/meta/llama-3.1-70b-instruct',
      messages: [
        {
          role: 'user',
          content: prompt
        }
      ]
    });

    res.status(200).json({ result: response.choices[0].message.content });
  } catch (error) {
    res.status(500).json({ error: error.message });
  }
}

Best Practices

1. Prompt Engineering

   • Be specific and detailed in requirements
   • Use system messages to set context
   • Break complex tasks into steps
   • Include examples for better results

2. Resource Optimization

   • Use streaming for long responses
   • Implement proper error handling
   • Cache common responses
   • Monitor token usage

3. Quality Control

   • Validate model outputs
   • Implement human review when needed
   • Use lower temperatures for factual responses
   • Higher temperatures for creative tasks

Token Management

Plan	Monthly Token Quota
Free Tier	40K tokens
$29 Plan	400K tokens
$49 Plan	600K tokens

When to Use

✅ Ideal For:

• Complex reasoning tasks
• Research and analysis
• Professional content creation
• Technical documentation
• System design
• Multi-step problem solving

❌ Consider Alternatives When:

• Quick responses needed
• Simple tasks
• Limited computing resources
• Cost-sensitive applications
• High-volume, basic operations

Getting Started

To begin using Llama-3.1-70B, check out:

• Quick Start Guide
• JavaScript SDK
• Python SDK