--- title: Llama 3.1 405B Turbo — Advanced Reasoning | ModelsLab description: Access Meta Llama 3.1 405B Instruct Turbo API for 128K context, function calling, and 80 tokens/sec inference. Generate complex responses via simple LLM... url: https://modelslab.com/meta-llama-31-405b-instruct-turbo canonical: https://modelslab.com/meta-llama-31-405b-instruct-turbo type: website component: Seo/ModelPage generated_at: 2026-04-15T02:06:56.545944Z --- Available now on ModelsLab · Language Model Meta Llama 3.1 405B Instruct Turbo Scale Intelligence Turbocharged --- [Try Meta Llama 3.1 405B Instruct Turbo](/models/meta/meta-llama-Meta-Llama-3.1-405B-Instruct-Turbo) [API Documentation](https://docs.modelslab.com) Deploy Frontier Capabilities Now --- 128K Context ### Handle Long Inputs Process 128,000 tokens for extended reasoning and document analysis in Meta Llama 3.1 405B Instruct Turbo. 80 Tokens/Second ### Turbo Inference Speed Achieve up to 80 tokens per second with Together Turbo on Meta Llama 3.1 405B Instruct Turbo model. Function Calling ### Integrate Tools Seamlessly Enable tool use, JSON mode, and zero-shot integration via Meta Llama 3.1 405B Instruct Turbo API. Examples See what Meta Llama 3.1 405B Instruct Turbo can create --- Copy any prompt below and try it yourself in the [playground](/models/meta/meta-llama-Meta-Llama-3.1-405B-Instruct-Turbo). Code Review “Review this Python function for bugs, optimize for performance, and suggest unit tests: def fibonacci(n): if n <= 1: return n return fibonacci(n-1) + fibonacci(n-2)” Data Analysis “Analyze this sales dataset JSON for trends, anomalies, and recommendations: \[{'month': 'Jan', 'sales': 1200}, {'month': 'Feb', 'sales': 1500}, {'month': 'Mar', 'sales': 900}\]” Tech Summary “Summarize key advancements in transformer architectures post-2023, focusing on efficiency and scaling laws, in 300 words.” Logic Puzzle “Solve this riddle step-by-step: Three houses in a row, owned by Alice, Bob, Carl. Alice has a dog, Bob has a cat, Carl has neither. The cat hates the dog. Who lives in the middle?” For Developers A few lines of code. Inference. Four lines. --- 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 405B Instruct Turbo --- [Read the docs ](https://docs.modelslab.com) ### What is Meta Llama 3.1 405B Instruct Turbo? ### How fast is Meta Llama 3.1 405B Instruct Turbo API? ### What is the context window for meta llama 3.1 405b instruct turbo model? ### Does Meta Llama 3.1 405B Instruct Turbo support function calling? ### Where to find Meta Llama 3.1 405B Instruct Turbo alternative? ### What are MMLU scores for Meta Llama 3.1 405B Instruct Turbo? Ready to create? --- Start generating with Meta Llama 3.1 405B Instruct Turbo on ModelsLab. [Try Meta Llama 3.1 405B Instruct Turbo](/models/meta/meta-llama-Meta-Llama-3.1-405B-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*