Llama
LLaMA (Large Language Model Meta AI) is Meta's open-source family of large language models offering scalable, multilingual, and multimodal capabilities that can be fine-tuned, distilled and deployed anywhere.
https://www.llama.com?ref=aipure
Product Information
Updated:May 16, 2025
Llama Monthly Traffic Trends
Llama achieved 1.7M visits with a 69.5% growth in July. The release of Llama 4 with a mixture of experts architecture and multimodal capabilities likely attracted more users, while the LlamaCon AI conference and new API further boosted interest and adoption.
What is Llama
LLaMA is a series of advanced artificial intelligence language models developed by Meta (formerly Facebook). Starting with LLaMA 1 in 2023 and evolving through LLaMA 2 to the current LLaMA 3 series, these models are designed to process and generate human-like text while supporting multiple languages. What sets LLaMA apart is its open-source nature, allowing researchers, developers, and organizations to freely access, modify, and build upon its capabilities, making it a cornerstone of democratized AI development.
Key Features of Llama
Llama is Meta's family of open-source large language models that offers multiple versions (3.1, 3.2, 3.3) with varying capabilities and sizes. It features multilingual support, multimodal abilities for image understanding, and lightweight versions for mobile/edge devices. The models range from 1B to 405B parameters and can be fine-tuned, distilled and deployed anywhere, making it accessible for both research and commercial purposes.
Multiple Model Variants: Offers different sized models from 1B to 405B parameters, including lightweight versions (1B, 3B), multimodal models (11B, 90B), and the flagship 405B model
Multimodal Capabilities: Llama 3.2 includes vision-enabled models that can understand images, read handwriting, and analyze visual data like charts and graphs
Comprehensive Development Stack: Includes Llama Stack with built-in safety features, tool calling capabilities, and support for multiple programming languages (Python, Node, Kotlin, Swift)
Multilingual Support: Supports numerous languages including Bulgarian, Catalan, Czech, Danish, German, English, Spanish, French, and many others
Use Cases of Llama
Mobile Applications: Lightweight models (1B, 3B) can run on mobile devices for tasks like discussion summarization and calendar management
Enterprise Data Privacy: Companies like Zoom use Llama for AI assistants that maintain data privacy while enhancing productivity through chat and meeting summaries
Document Analysis: Can extract and summarize information from documents containing images, graphs, and charts for business intelligence
Code Development: Used by companies like DoorDash for code review and answering complex technical questions
Pros
Open source and freely available for research and commercial use
Flexible deployment options (on-premise, cloud, or edge devices)
Strong multilingual and multimodal capabilities
Cons
Requires significant computational resources for larger models
May need fine-tuning for specific use cases
How to Use Llama
Choose a Llama Access Method: Select from multiple options: Hugging Face, GPT4ALL, Ollama, or direct download from Meta AI's official website
Set Up Environment: Install necessary tools based on chosen method. For example, if using GPT4ALL, download and install the application from the official download page
Select Llama Model: Choose from available models: Llama 3.1 (8B, 405B), Llama 3.2 (1B, 3B, 11B, 90B), or Llama 3.3 (70B) based on your needs and computational resources
Download Model: Download the selected model. For GPT4ALL, use the Downloads menu and select Llama model. For Hugging Face, access through their platform interface
Configure Settings: Set up parameters like maximum tokens, temperature, and other model-specific settings depending on your use case
Integration: Integrate the model into your application using provided APIs or SDKs. Choose from Python, Node, Kotlin, or Swift programming languages
Test Implementation: Start with basic prompts to test the model's functionality and adjust settings as needed for optimal performance
Deploy: Deploy your implementation either locally, on-premises, cloud-hosted, or on-device at the edge depending on your requirements
Llama FAQs
Llama is a family of open-source AI models developed by Meta that can be fine-tuned, distilled and deployed anywhere. It includes multilingual text-only models, text-image models, and various sizes of models optimized for different use cases.
Analytics of Llama Website
Llama Traffic & Rankings
1.7M
Monthly Visits
#37509
Global Rank
#676
Category Rank
Traffic Trends: Nov 2024-Apr 2025
Llama User Insights
00:01:34
Avg. Visit Duration
2.06
Pages Per Visit
53.38%
User Bounce Rate
Top Regions of Llama
US: 26.18%
IN: 9.79%
BR: 4.49%
GB: 3.67%
KR: 3.26%
Others: 52.6%
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