--- title: Llama 3.1 70B Turbo — Fast LLM | ModelsLab description: Run Meta Llama 3.1 70B Instruct Turbo for 131k context and function calling. Generate complex responses via API now. url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/meta-llama-31-70b-instruct-turbo canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/meta-llama-31-70b-instruct-turbo type: website component: Seo/ModelPage generated_at: 2026-05-13T09:43:59.136667Z --- Available now on ModelsLab · Language Model Meta Llama 3.1 70B Instruct Turbo Turbocharge Llama Inference --- [Try Meta Llama 3.1 70B Instruct Turbo](/models/meta/meta-llama-Meta-Llama-3.1-70B-Instruct-Turbo) [API Documentation](https://docs.modelslab.com) 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](/models/meta/meta-llama-Meta-Llama-3.1-70B-Instruct-Turbo). 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 ](https://docs.modelslab.com) PythonJavaScriptcURL Copy ```

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 ](https://docs.modelslab.com) ### What is Meta Llama 3.1 70B Instruct Turbo? 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. ### How does Meta Llama 3.1 70B Instruct Turbo API compare to alternatives? 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. ### What context length supports meta llama 3.1 70b instruct turbo model? 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. ### Does Meta Llama 3.1 70B Instruct Turbo support function calling? 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. ### What pricing for meta llama 3.1 70b instruct turbo api? 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. ### Is Meta Llama 3.1 70B Instruct Turbo multilingual? 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 Turbo](/models/meta/meta-llama-Meta-Llama-3.1-70B-Instruct-Turbo) [API Documentation](https://docs.modelslab.com) --- *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) --- *Generated by ModelsLab - 2026-05-13*