--- title: Llama 3.3 70B Turbo — Fast Instruct LLM | ModelsLab description: Access Meta Llama 3.3 70B Instruct Turbo API for function calling and 131K context. Generate precise multilingual responses via simple LLM endpoint. url: https://modelslab.com/meta-llama-33-70b-instruct-turbo canonical: https://modelslab.com/meta-llama-33-70b-instruct-turbo type: website component: Seo/ModelPage generated_at: 2026-04-15T02:06:21.688594Z --- Available now on ModelsLab · Language Model Meta Llama 3.3 70B Instruct Turbo Turbocharge Llama Inference --- [Try Meta Llama 3.3 70B Instruct Turbo](/models/meta/meta-llama-Llama-3.3-70B-Instruct-Turbo) [API Documentation](https://docs.modelslab.com) Run Llama 3.3 Turbo Now --- 131K Context ### Massive Token Window Handles 131K input and output tokens for long-context tasks. Function Calling ### Tool Integration Ready Supports structured function calls in Meta Llama 3.3 70B Instruct Turbo API. Cost Efficient ### Low Token Pricing Starts at $0.1/M input, $0.32/M output on select providers. Examples See what Meta Llama 3.3 70B Instruct Turbo can create --- Copy any prompt below and try it yourself in the [playground](/models/meta/meta-llama-Llama-3.3-70B-Instruct-Turbo). Code Review “<|begin\_of\_text|><|start\_header\_id|>system<|end\_header\_id|>You are a senior software engineer. Review this Python code for bugs and optimizations.<|eot\_id|><|start\_header\_id|>user<|end\_header\_id|>def fibonacci(n): if n <= 1: return n return fibonacci(n-1) + fibonacci(n-2) print(fibonacci(10))<|eot\_id|>” SQL Query “<|begin\_of\_text|><|start\_header\_id|>system<|end\_header\_id|>You are a database expert. Write efficient SQL for this schema.<|eot\_id|><|start\_header\_id|>user<|end\_header\_id|>Schema: users(id, name, email). Find users with gmail addresses, ordered by name.<|eot\_id|>” JSON Schema “<|begin\_of\_text|><|start\_header\_id|>system<|end\_header\_id|>Generate valid JSON schemas for APIs.<|eot\_id|><|start\_header\_id|>user<|end\_header\_id|>Create schema for a product catalog with id, name, price, and tags array.<|eot\_id|>” Math Proof “<|begin\_of\_text|><|start\_header\_id|>system<|end\_header\_id|>You are a mathematician. Provide step-by-step proofs.<|eot\_id|><|start\_header\_id|>user<|end\_header\_id|>Prove that the sum of first n odd numbers equals n squared.<|eot\_id|>” For Developers A few lines of code. Instruct Turbo. 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 3.3 70B Instruct Turbo --- [Read the docs ](https://docs.modelslab.com) ### What is Meta Llama 3.3 70B Instruct Turbo? ### How does Meta Llama 3.3 70B Instruct Turbo API compare to Llama 3.1? ### What is the pricing for meta llama 3.3 70b instruct turbo model? ### Does Meta Llama 3.3 70B Instruct Turbo support function calling? ### Is Meta Llama 3.3 70B Instruct Turbo a good alternative? ### What providers host meta llama 3.3 70b instruct turbo api? Ready to create? --- Start generating with Meta Llama 3.3 70B Instruct Turbo on ModelsLab. [Try Meta Llama 3.3 70B Instruct Turbo](/models/meta/meta-llama-Llama-3.3-70B-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 - 2026-04-15*