Llama is a family of open large language models developed by Meta AI, designed to empower developers and researchers to build a wide range of AI applications.

How much does Llama cost?

Llama models are available for free for both research and commercial use, making them accessible for broad adoption.

Llama models can be used for various natural language processing tasks, including text generation, summarization, translation, and building conversational AI systems.

Is Llama open source?

While Llama models are openly available, the GitHub repository indicates 'NOASSERTION' for the license, meaning it does not explicitly state an OSI-approved open-source license.

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Llama

Open models for developers

Backed by Meta AI

Highly customizable

Requires technical expertise

A family of open large language models designed for developers.

Last updated: May 30, 2026

FREEMIUM

llama.meta.com

Quick Answer

Llama is a family of open large language models from Meta AI, designed for developers and researchers to build AI applications. It offers various model sizes and is available for free for both research and commercial use, providing a flexible foundation for custom AI solutions.

About Llama

Llama is a collection of state-of-the-art open large language models developed by Meta AI, designed for a wide range of applications from research to commercial deployment. It offers various model sizes to suit different computational needs and use cases. Available for free for research and commercial use.

What Makes It Unique

Llama models are developed by Meta AI and are available as open models, allowing for broad access and customization for various applications, distinguishing them from many proprietary alternatives.

AI-extracted from public sources. May contain errors. Methodology · Are you Llama? Claim listing

Use Cases & Target Users

Use Cases

Software Development

Best For

Developing AI-powered applications

Conducting AI research and experimentation

Building custom large language models

Integrating advanced natural language capabilities

Company Size

SOLO

SMALL

MEDIUM

ENTERPRISE

Fit Score

Complexity

Advanced

Target Team Size

INDIVIDUAL

SMALL_TEAM

LARGE_TEAM

Target Skill Level

EXPERT

Key Features

Chat completion: Generate text from a prompt or build chat-based AI assistants using multi-modal input (text, images) and text-based outputs.

Image understanding: Process and analyze visual data to extract insights, interpret charts, and more.

JSON structured output: Generate responses that follow pre-defined JSON schemas.

Tool calling: Integrate with existing tools by defining functions that can be called when generating responses.

Multi-modal capabilities: Natively processes text and images, enabling advanced use cases like visual question answering. Llama 4 models also support video and audio.

Code generation and debugging: Specialized Code Llama models are fine-tuned for programming tasks.

Technical Specifications

API Available

SDK Available

MCP Compatible

Open Source

Team Features

SSO/Enterprise

Webhook Support

Has Demo

Function Calling

Browser Extension

Sandbox Mode

Audit Logs

Free Plan

No Signup

Works Offline

Requires Host App

Framework

MCP Server

IDE Plugin

Inference API

SCIM Provisioning

Developer Access

API

ENTERPRISE

SDK

Deployment:

SELF_HOSTED

Uses models:1

Pros

+Openly available for research and commercial use
+Backed by Meta AI's research
+Offers various model sizes for flexibility
+Strong community support due to open nature

Limitations

-Requires technical expertise for deployment and fine-tuning
-Performance depends on hardware resources
-May require significant data for fine-tuning specific tasks

Powered By

Base Models

Llama 3

Uses Models

Llama 3

Decision Intelligence

Best For

Developing AI-powered applications

Conducting AI research and experimentation

Building custom large language models

Integrating advanced natural language capabilities

Not Ideal For

Non-technical users seeking a ready-to-use AI chatbot

Users without programming or machine learning experience

Simple, out-of-the-box content generation without customization

Frequently Asked Questions

Your Actions

Dimension Scores

Ease of Use3/10

Output Quality8/10

Value for Money10/10

Customization5/10

Support7/10

Integration1/10

Task Scores

Code Completion

8

Context Understanding

8

Bug Detection

7

Code Explanation

7

Refactoring

7

Multi Language Support

7

Documentation Generation

7

Performance Optimization

7

Trust Score

23/100

Limited Data

Based on 4 data signals

Reflects publicly available data, not an independent audit

Company Strength15/25

Team Size5000+

Company ListedMeta

Operational Trust8/20

Data ResidencyMulti-cloud availability with native hosting and support on Amazon Bedrock and Google Vertex AI Model Garden, allowing for data residency requirements.

Open Source29.3K stars

Benchmark Performance

Independent third-party evaluation results across 1 benchmarks

Composite

HELM Lite Mean

Stanford CRFM 2024 · Stanford HELM

0.3446441947565543

34.46441947565543th pct

HELM-Lite mean win rate (v1.13.0)

5/24/2026·source

Scores from official leaderboards or vendor-reported. Percentile is cross-benchmark normalized when populated by an aggregator. See methodology.

Switching & Migration

Migration Difficulty

Moderate Effort

Developer-friendly interface, community support, and official SDKs.

API Access

Quick Stats

CategorySoftware Development

PlatformsAPI, CLI

Integrations0+

LaunchedFeb 2023

AddedMar 2026

Company & Links

CompanyMeta

Documentation

LinkedIn Twitter/X

AI Tools

AI Tools

Llama

Quick Answer

Decision Intelligence

Best For

Not Ideal For

Frequently Asked Questions

What is Llama?

How much does Llama cost?

What can Llama do?

Is Llama open source?

Who developed Llama?

Dimension Scores

Task Scores

Trust Score

Benchmark Performance

Composite

Switching & Migration