Meta Llama 3.1 405B Instruct Turbo
Scale Intelligence Turbocharged
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.
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
import requestsresponse = requests.post("https://modelslab.com/api/v7/llm/chat/completions",json={"key": "YOUR_API_KEY","prompt": "","model_id": ""})print(response.json())
Ready to create?
Start generating with Meta Llama 3.1 405B Instruct Turbo on ModelsLab.