Name: Llama 3.3 70B Instruct Turbo API
Brand: Meta

Overview

Meta Llama 3.3 70B Instruct Turbo Description

Basic Information

Model Name: Meta Llama 3.3 70B Instruct Turbo
Developer/Creator: Meta Platforms, Inc.
Release Date: December 6, 2024
Version: 1.0
Model Type: Large Language Model (LLM)

Overview:

Meta Llama 3.3 70B Instruct Turbo is a highly optimized large language model designed for efficient text generation and instruction-following tasks. Leveraging advanced AI techniques, this model aims to deliver high-quality outputs with improved inference speeds while maintaining a focus on safety and flexibility.

Key Features:

Optimized Performance: Utilizes FP8 quantization for significantly faster inference speeds with only a minor trade-off in accuracy.
Large Context Window: Supports an extensive context length, allowing for more comprehensive interactions and detailed responses.
Instruction Tuning: Specifically tuned for instruction-following tasks, making it suitable for applications requiring conversational capabilities and task-oriented responses.
State-of-the-Art Benchmarks: Achieves top performance across various benchmarks, including conversational tasks, language translation, and text generation.
Safety and Mitigation: Designed with a focus on responsible deployment to mitigate risks such as bias, toxicity, and misinformation.

Intended Use:

The model is intended for developers and researchers looking to implement advanced natural language processing capabilities in applications such as chatbots, virtual assistants, content creation tools, and educational software.

Language Support:

Meta Llama 3.3 supports multiple languages, enhancing its usability in global applications and diverse linguistic contexts.

Technical Details

Architecture:

Meta Llama 3.3 employs a transformer architecture optimized for performance through techniques such as FP8 quantization. This architecture allows the model to efficiently process large amounts of text while maintaining high-quality output.

Training Data:

The model was trained on a diverse dataset sourced from various publicly available texts to ensure robust performance across different scenarios.

Data Source and Size: The training dataset includes a wide range of topics and genres, although specific sizes are not disclosed.
Knowledge Cutoff: The model's knowledge is current as of December 2023.
Diversity and Bias: The training data was curated to minimize biases while maximizing diversity in topics and styles, contributing to the model's overall effectiveness.

Performance Metrics and Comparison to Other Models:

Meta Llama 3.3 has demonstrated strong performance metrics:

Benchmark	Llama 3.1 8B Instruct	Llama 3.1 70B Instruct	Llama-3.3 70B Instruct	Llama 3.1 405B Instruct
MMLU (CoT)	73.0	86.0	86.0	88.6
MMLU Pro (CoT)	48.3	66.4	68.9	73.3
IFEval	80.4	87.5	92.1	88.6
GPQA Diamond (CoT)	31.8	48.0	50.5	49.0
HumanEval	72.6	80.5	88.4	89.0
MBPP EvalPlus (base)	72.8	86.0	87.6	88.6
MATH (CoT)	51.9	68.0	77.0	73.8
BFCL v2	65.4	77.5	77.3	81.1
MGSM	68.9	86.9	91.1	91.6

Usage

Code Samples:

The model is available on the AI/ML API platform as "Meta Llama 3.3 70B Instruct Turbo" .

API Documentation:

Detailed API Documentation is available here.

Ethical Guidelines

Meta emphasizes ethical considerations in AI development by promoting transparency regarding the model's capabilities and limitations. The organization encourages responsible usage to prevent misuse or harmful applications of generated content.

Licensing

The Meta Llama 3.3 models are available under a community license that allows both research and commercial usage rights while ensuring compliance with ethical standards regarding creator rights.

Get Meta Llama 3.3 70B Instruct Turbo API here.

Use cases

enterprise chatbots and virtual assistants with long-context retention
multilingual customer service automation and support
software development assistance including code writing and debugging
content creation for marketing, technical writing, and creative applications
extended conversational agents for research and education
document summarization and knowledge extraction for large corpora
translation and multilingual NLP applications

How to use Llama 3.3 70B Instruct Turbo API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to meta-llama/Llama-3.3-70B-Instruct-Turbo.

import requests

r = requests.post(
    "https://api.aimlapi.com/v1/chat/completions",
    headers={"Authorization": "Bearer " + AIMLAPI_KEY},
    json={
      "model": "meta-llama/Llama-3.3-70B-Instruct-Turbo",
      "messages": [
        {
          "role": "user",
          "content": "Hello!"
        }
      ]
    },
)
print(r.json())

const r = await fetch("https://api.aimlapi.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "meta-llama/Llama-3.3-70B-Instruct-Turbo",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }),
});
console.log(await r.json());

curl -X POST https://api.aimlapi.com/v1/chat/completions \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"meta-llama/Llama-3.3-70B-Instruct-Turbo","messages":[{"role":"user","content":"Hello!"}]}'

OpenAI-compatible — swap the base URL and it works with your existing SDK.