Meta: Llama 3.3 70B Instruct
Reason Smarter. Scale Efficiently
Unlock Llama 3.3 Power
70B Parameters
Outperforms Larger Models
Meta: Llama 3.3 70B Instruct matches Llama 3.1 405B on reasoning and coding with lower compute needs.
128K Context
Handles Long Inputs
Supports 128,000 token context for extended dialogues and complex instruction chains.
Multilingual Support
Excels Instruction Following
Meta: Llama 3.3 70B Instruct API delivers top scores in coding, math, and tool use across languages.
Examples
See what Meta: Llama 3.3 70B Instruct can create
Copy any prompt below and try it yourself in the playground.
Code Debugger
“Debug this Python function that calculates Fibonacci numbers inefficiently. Provide optimized version with explanations and test cases.”
Reasoning Chain
“Solve: A bat and ball cost $1.10 total. Bat costs $1 more than ball. How much is the ball? Explain step-by-step.”
JSON Function Call
“Generate weather query JSON for function call: city=London, units=metric. Include error handling.”
Multilingual Translation
“Translate this technical doc excerpt from English to Spanish and German, preserving code snippets and terminology.”
For Developers
A few lines of code.
Instruct model. One API 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
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 3.3 70B Instruct on ModelsLab.