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Available now on ModelsLab · Language Model

Meta Llama 3.1 70B Instruct TurboTurbocharge Llama Inference

Try Meta Llama 3.1 70B Instruct TurboAPI Documentation

Deploy Turbo Performance

131K Context

Handle Long Inputs

Process 131k input and output tokens for extended dialogues and documents.

Function Calling

Integrate Tools Seamlessly

Call external functions directly in Meta Llama 3.1 70B Instruct Turbo API responses.

Cost Efficient

Scale Without Breaking Bank

Access Meta Llama 3.1 70B Instruct Turbo model at $0.4 per million tokens.

Examples

See what Meta Llama 3.1 70B Instruct Turbo can create

Copy any prompt below and try it yourself in the playground.

Code Review

“Review this Python function for bugs and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2). Provide refactored code with memoization.”

Document Summary

“Summarize key points from this 10k token research paper on quantum computing advancements, focusing on practical applications and limitations. Extract main claims and evidence.”

Multilingual Translation

“Translate this technical spec from English to Spanish, German, and Hindi while preserving code snippets: 'API endpoint: POST /v1/completions with JSON payload {model: "llama", prompt: "hello"}'.”

JSON Generation

“Generate a valid JSON schema for a user profile API including fields for name, email, preferences array, and nested address object. Include validation rules.”

For Developers

A few lines of code.
Turbo 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 
import requests


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

FAQ

Common questions about Meta Llama 3.1 70B Instruct Turbo

Read the docs

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Try Meta Llama 3.1 70B Instruct TurboAPI Documentation