The wait is finally over! Mark Zuckerberg just unveiled LLaMA 3.2 at the Meta Connect event, and it’s packed with features that you’ll definitely want to check out. This new model is designed to push the boundaries of artificial intelligence (AI) and is perfect for a variety of applications, from healthcare to digital marketing.
Here’s what you need to know about this exciting release of Llama 3.2 11B Vision Instruct Turbo, Llama 3.2 90B Vision Instruct Turbo, Llama 3.2 3B Instruct Turbo and other LLaMA 3.2 models.
LLaMA 3.2 stands out because it can understand and respond to both text and images. You can upload an image and ask questions about it, and the model will provide relevant answers. This makes it more versatile than traditional models that only handle text or images separately.
One of the biggest highlights is that LLaMA 3.2 can run smoothly on mobile devices and edge hardware like Qualcomm and ARM processors. Meta has also released templates to help developers create apps using Swift, making it easier than ever to use this technology in mobile applications.
LLaMA 3.2 comes in several sizes to fit your needs:
Meta offers both pre-trained models and instruction fine-tuned versions. This means developers and researchers can easily adapt these models for specific tasks without starting from scratch.
LLaMA 3.2 has been tested and scored impressively on various benchmarks:
This shows how capable LLaMA 3.2 is in understanding complex visual content, which is essential for areas like healthcare diagnostics and automation.
Meta is encouraging developers to use the LLaMA Stack, which provides various tools for batch and real-time inference and fine-tuning. Plus, LLaMA 3.2 supports multiple programming languages like Python, Node.js, and Swift, giving developers everything they need to create AI-driven applications.
The model also supports several languages for text tasks, including English, German, French, Italian, Portuguese, Hindi, and Thai. While English is the main language for image-text tasks, the model can be fine-tuned for other languages in the future.
The 1B and 3B parameter models are distilled versions of the larger 90B model. This means they have been optimized for high performance without requiring full retraining, making them efficient for specific tasks.
LLaMA 3.2 is being marketed as an open-weight model, but it does come with some licensing restrictions. Fortunately, most businesses and developers shouldn’t face any issues unless they’re scaling to very large user bases.
Meta even showcased a demo of a deepfake assistant powered by LLaMA 3.2, where users could have real-time conversations with a digital twin!
With LLaMA 3.2, the possibilities are endless!
Shoppers can upload images of products they like, and LLaMA 3.2 will find similar items available for purchase, making shopping easier and more personalized.
Students can ask questions about images in their textbooks, receiving detailed explanations that enhance their understanding and engagement.
LLaMA 3.2 can help doctors quickly analyze X-rays and MRIs, identifying issues like fractures or tumors to enhance patient care.
For example, analysis for Llama-3.2 90B, 11B, 3B, and 1B for Medical & Healthcare Domain showed:
🥇 Llama-3.1 70B Instruct is a top performer with an average score of 84% (MMLU College Biology, MMLU Professional Medicine)
🥈 Meta-Llama-3.2-90B-Vision (Instruct and Base) takes second place with an average score of 83.95%
🥉 Meta-Llama-3-70B-Instruct is on the third place with an average score of 82.24% (MMLU Medical Genetics, MMLU College Biology)
LLaMA 3.2 can analyze live video feeds to detect unusual behavior or potential threats, improving safety in public spaces.
Conservationists can use LLaMA 3.2 to analyze drone footage for monitoring animal populations and detecting poaching activities in real-time.
With LLaMA 3.2, Meta is solidifying its place at the forefront of multimodal AI technology. Whether you’re a developer looking to create mobile applications or a researcher exploring niche tasks, LLaMA 3.2 provides the flexibility and power you need.
Ready to dive in? You can access the LLaMA 3.2 models and over 200 others through the AI/ML API.
Test LLaMA 3.2 for FREE with the snippet below
import os
from together import Together
client = Together(base_url="https://api.aimlapi.com/v1", api_key="<YOUR_API_KEY>")
response = client.chat.completions.create(
model="meta-llama/Llama-Vision-Free",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "What sort of animal is in this picture? What is its usual diet? What area is
the animal native to? And isn’t there some AI model that’s related to the image?",
},
{
"type": "image_url",
"image_url": {
"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/3/3a/LLama.jpg/444px-
LLama.jpg?20050123205659",
},
},
],
}
],
max_tokens=300,
)
print("Assistant: ", response.choices[0].message.content)