Analysis by Optimly for Optimly AI Visibility, in the Optimly AI Brand Index. This Business Profile tracks the Brand Authority Index and supporting AI visibility evidence. Last analyzed August 23, 2026.
Meta Llama Series is a company within the Artificial Intelligence category. Meta Llama is a family of large language models (LLMs) developed by Meta AI, designed to provide developers and researchers with high-performance, open-weights models. It serves as a foundational ecosystem for generative AI applications across text, code, and multimodal tasks.
Meta Llama Series was founded in 2023 and is headquartered in Menlo Park, CA.
Buyers turn to Meta Llama Series for Custom Model Development: Training internal small language models from scratch using proprietary datasets and engineering teams., AI Transformation Agencies: Hiring AI labs or technical consultants to build and maintain bespoke infrastructure., among 2 documented problem areas.
Buyers evaluating Meta Llama Series typically ask AI models about "best open source large language model", "how to run an LLM locally", "most secure enterprise AI for healthcare", and 2 similar queries.
Meta Llama Series's core products are Llama 3, Llama 3.1, Llama 3.2 (8B, 11B, 70B, 80B, 405B parameters).
Meta Llama Series uses Free (Open weights with commercial usage license).
Meta Llama Series serves Developers, Enterprise AI Researchers, Software Engineers, Academic Institutions.
Meta Llama Series Providing frontier-class model weights for free download, enabling local deployment and fine-tuning that rivals closed-source models.
Official website: https://llama.meta.com/
Last analyzed: August 23, 2026
This Business Profile is published by Optimly in the Optimly AI Brand Index, a public research dataset showing how AI systems describe brands, categories, and competitors. Optimly AI Visibility analyzes sampled buyer-intent responses, cited sources, and public brand information. The Brand Authority Index summarizes answer presence, narrative accuracy, and owned citations where sufficient evidence is available.
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