Llama

WebsiteContact for PricingLarge Language Models (LLMs)
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.
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Llama

Product Information

Updated:Jun 9, 2025

Llama Monthly Traffic Trends

Llama experienced a 40.9% decline in traffic, likely due to delays in the release of its latest version, Llama 4, and lukewarm reception from developers. The delayed release of Llama 4 and concerns about its performance compared to competitors may have contributed to the drop in user engagement.

View history traffic

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
984.8K
Monthly Visits
#61436
Global Rank
#608
Category Rank
Traffic Trends: Nov 2024-May 2025
Llama User Insights
00:00:59
Avg. Visit Duration
1.87
Pages Per Visit
50.46%
User Bounce Rate
Top Regions of Llama

  1. US: 23.53%

  2. IN: 11.02%

  3. GB: 3.37%

  4. KR: 3.15%

  5. BR: 3.11%

  6. Others: 55.83%

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