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Meta: Llama 3.3 70B InstructReason Smarter. Scale Efficiently

Try Meta: Llama 3.3 70B InstructAPI Documentation

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
API Documentation 
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

Read the docs

Meta: Llama 3.3 70B Instruct is a 70B parameter text-only LLM optimized for instruction following and multilingual dialogue. It outperforms Llama 3.1 70B in reasoning, coding, and math tasks.

Meta: Llama 3.3 70B Instruct delivers comparable performance to Llama 3.1 405B at lower cost and hardware demands. It excels in instruction following with 92.1 IFEval score.

Meta: Llama 3.3 70B Instruct model handles 128,000 tokens for prompts and responses. On-demand runs cap responses at 4,000 tokens.

Yes, Meta: Llama 3.3 70B Instruct LLM supports English, German, French, Spanish, Hindi, Thai, and more. It generates text and code in multiple languages.

As an open-source alternative, meta llama 3.3 70b instruct provides strong tool use, JSON output for functions, and code error fixing. Use via LLM endpoints for chatbots and assistants.

Integrate Meta: Llama 3.3 70B Instruct API through compatible LLM endpoints like OpenAI SDK. It's available for on-demand inference and fine-tuning.

Ready to create?

Start generating with Meta: Llama 3.3 70B Instruct on ModelsLab.

Try Meta: Llama 3.3 70B InstructAPI Documentation