Neura Market
Llama 4 logo

Llama 4

Paid

Open-source multimodal LLM family from Meta

4.4
New AI ToolsContact
Inputs: text, imageOutputs: text
Type
Saas
Visit Website

About Llama 4

Llama 4 is a family of open-source multimodal large language models developed by Meta. The family includes two primary variants: Scout and Maverick. Scout is described as supporting an exceptionally long context window of up to 10 million tokens, while Maverick is reported to surpass the performance of GPT-4o. Both models utilize a Mixture of Experts (MoE) architecture and natively fuse text and image inputs, enabling them to process and reason over visual and textual data jointly. The models are positioned for a variety of advanced AI tasks, including visual question answering, document analysis, and long-context reasoning. As an open-source offering, Llama 4 aims to provide access to state-of-the-art multimodal capabilities for developers and researchers, though specific usage terms and availability should be verified through official channels.

Key Features

Open-source multimodal LLM family (Scout and Maverick variants)
Mixture of Experts (MoE) architecture for efficient scaling
Native text and image fusion for joint visual and language understanding
Scout variant supports up to 10 million token context window
Maverick variant claims performance surpassing GPT-4o
Publicly available via Hugging Face and other platforms (based on listing)

Pros & Cons

Pros
  • Open-source release allows for customization and local deployment
  • Impressive long-context capability (up to 10M tokens) in Scout variant
  • Strong reported performance, with Maverick surpassing GPT-4o
  • MoE architecture may offer efficiency advantages for some tasks
Cons
  • Pricing model listed as 'contact' suggests commercial use may require a paid license; free access details should be verified
  • Requires significant computational resources for local deployment, especially with long contexts
  • Availability and stability of Maverick variant may depend on phased rollout
  • Bias and safety characteristics of the models have not been detailed in the available description
  • Not a turnkey SaaS; users need technical expertise to deploy and use the models

Best For

Visual question answering on images and documentsLong-document summarization and analysis with massive contextImage captioning and description generationMultimodal reasoning for research and developmentBuilding custom AI applications requiring text+image understandingBenchmarking and academic research in open-source AI

Alternatives to Llama 4

PlugSugar

Automate conversations, answer questions with Web Search plugin, and customize ChatGPT experience using powerful AI plugins.

Respage

Automate lead acquisition, interact with potential leads, and capture lead information and preferences.

Travel Plan AI

Your personal AI guide for unforgettable journeys.

3D Avataaars Generator

Create custom avatars for storytelling, game development, and marketing campaigns with ease.

Voice Control for ChatGPT

Expands ChatGPT with fast voice control in multiple languages, read aloud, and more!

Folk AI

The CRM that works for your team

FAQ

What is Llama 4?
Based on available information, Llama 4 is a family of open-source multimodal large language models developed by Meta. It includes two variants: Scout (with a 10M token context window) and Maverick (which reportedly surpasses GPT-4o). The models use a Mixture of Experts architecture and natively fuse text and image inputs.
Is Llama 4 free to use?
The listing indicates a pricing model of 'contact' for the tool. While the models are open-source and may be freely accessible for research, commercial usage or API access might require a paid arrangement. Exact terms should be verified on official Meta channels.
What are the main differences between Scout and Maverick?
Scout is described as having an exceptionally long context window of up to 10 million tokens, while Maverick is reported to achieve performance surpassing GPT-4o. The specific architectural or training differences are not detailed in the available content.
Can Llama 4 generate images?
Based on the description, Llama 4 focuses on native text and image fusion, meaning it can process and understand images alongside text. It is not explicitly described as an image generation model; output is primarily text-based, such as answers or captions.
Where can I download or access Llama 4?
The listing provides a link to the official Meta AI website and to Hugging Face. The models are likely available for download on Hugging Face under an open-source license. Specific terms and conditions should be checked on those platforms.
What hardware is recommended for running Llama 4?
Given the model sizes and long-context capability, running Llama 4, especially Scout with its 10M token context, requires substantial GPU memory and compute. Optimal hardware requirements should be confirmed in the model card or official documentation.