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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

Meta Llama 3.1 70B Instruct Turbo is a 70B parameter LLM optimized for instruction following with 131k context. It supports function calling and multilingual text generation. Released as a turbo variant for faster inference.

Meta Llama 3.1 70B Instruct Turbo API offers 131k context at lower cost than similar 70B models. It outperforms base Llama 3.1 70B in speed with FP8 quantization. Use as cost-efficient alternative for production.

The meta llama 3.1 70b instruct turbo model handles 131k input and output tokens. This enables long-form summarization and agent workflows. Max output reaches 131k in some providers.

Yes, Meta Llama 3.1 70B Instruct Turbo includes native function calling. Integrate tools like APIs or databases in responses. Confirmed across DeepInfra and Together AI hosts.

Pricing starts at $0.4 per million input/output tokens via DeepInfra. Together AI lists $0.88 per million. Varies by provider; check for cached input discounts.

Yes, trained on multilingual data supporting English, German, French, Spanish, Hindi, and more. Handles text and code in multiple languages. Optimized for dialogue use cases.

Ready to create?

Start generating with Meta Llama 3.1 70B Instruct Turbo on ModelsLab.

Try Meta Llama 3.1 70B Instruct TurboAPI Documentation