Wikiprompt

LLaMA

LLaMA (Large Language Model Meta AI) is a family of large language models released by Meta AI starting in February 2023, ranging from 1 billion to 2 trillion parameters, with versions including Llama 1, 2, 3, and 4.

LLaMA (Large Language Model Meta AI, serving as a backronym) is a family of large language models (LLMs) released by Meta AI starting in February 2023. The models come in various sizes, ranging from 1 billion to 2 trillion parameters. Initially released as a foundation model, starting with Llama 2, Meta AI also released instruction fine-tuned versions alongside the foundation models. The latest version is Llama 4, released in April 2025. In April 2026, Meta Superintelligence Labs released Muse Spark as a replacement for Llama.

Background

After the release of large language models such as GPT-3, a focus of research was up-scaling models, which in some instances showed major increases in emergent capabilities. The release of ChatGPT and its surprise success caused an increase in attention to large language models. Compared with other responses to ChatGPT, Meta's Chief AI scientist Yann LeCun stated that large language models are best for aiding with writing.

Versions

Initial release

The first version of Llama (stylized as LLaMA and sometimes referred to as Llama 1) was announced on February 24, 2023, via a blog post and a paper describing the model's training, architecture, and performance. The inference code used to run the model was publicly released under the open-source GPLv3 license. Access to the model's weights was managed by an application process, with access to be granted "on a case-by-case basis to academic researchers; those affiliated with organizations in government, civil society, and academia; and industry research laboratories around the world".

Llama was trained on only publicly available information, and was trained at various model sizes, with the intention to make it more accessible to different hardware. The model was exclusively a foundation model, although the paper contained examples of instruction fine-tuned versions of the model. Meta AI reported the 13B parameter model performance on most NLP benchmarks exceeded that of the much larger GPT-3 (with 175B parameters), and the largest 65B model was competitive with state of the art models such as PaLM and Chinchilla.

#### Leak

On March 3, 2023, a torrent containing Llama's weights was uploaded, with a link to the torrent shared on the 4chan imageboard and subsequently spread through online AI communities. That same day, a pull request on the main Llama repository was opened, requesting to add the magnet link to the official documentation. On March 4, a pull request was opened to add links to HuggingFace repositories containing the model. On March 6, Meta filed takedown requests to remove the HuggingFace repositories linked in the pull request, characterizing it as "unauthorized distribution" of the model. HuggingFace complied with the requests. On March 20, Meta filed a DMCA takedown request for copyright infringement against a repository containing a script that downloaded Llama from a mirror, and GitHub complied the next day.

Reactions to the leak varied. Some speculated that the model would be used for malicious purposes, such as more sophisticated spam. Some have celebrated the model's accessibility, as well as the fact that smaller versions of the model can be run relatively cheaply, suggesting that this will promote the flourishing of additional research developments. Multiple commentators, such as Simon Willison, compared Llama to Stable Diffusion, a text-to-image model which, unlike comparably sophisticated models which preceded it, was openly distributed, leading to a rapid proliferation of associated tools, techniques, and software.

Llama 2

On July 18, 2023, in partnership with Microsoft, Meta announced Llama 2 (stylized as LLaMa 2), the next generation of Llama. Meta trained and released Llama 2 in three model sizes: 7, 13, and 70 billion parameters. The model architecture remains largely unchanged from that of Llama 1 models, but 40% more data was used to train the foundational models.

Llama 2 includes foundation models and models fine-tuned for chat. In a further departure from the original version of Llama, all models are released with weights and may be used for many commercial use cases. Because Llama's license enforces an acceptable use policy that prohibits Llama from being used for some purposes, it is not open source. Meta's use of the term open-source to describe Llama has been disputed by the Open Source Initiative (which maintains The Open Source Definition) and others.

Code Llama is a fine-tune of Llama 2 with code specific datasets. 7B, 13B, and 34B versions were released on August 24, 2023, with a 70B version released on January 29, 2024. Starting with the foundation models from Llama 2, Meta AI would train an additional 500B tokens of code datasets, before an additional 20B token of long-context data, creating the Code Llama foundation models. This foundation model was further trained on 5B instruction following token to create the instruct fine-tune. Another foundation model was created for Python code, which trained on 100B tokens of Python-only code, before the long-context data.

Llama 3

On April 18, 2024, Meta released Llama 3 with two sizes: 8B and 70B parameters. The models have been pre-trained on approximately 15 trillion tokens of text gathered from "publicly available sources" with the instruct models fine-tuned on "publicly available instruction datasets, as well as over 10M human-annotated examples". Meta AI's testing showed in April 2024 that Llama 3 70B was beating Gemini Pro 1.5 and Claude 3 Sonnet on most benchmarks. Meta also announced plans to make Llama 3 multilingual and multimodal, better at coding and reasoning, and to increase its context window.

Regarding scaling laws, Llama 3 models empirically showed that when a model is trained on data that is more than the "Chinchilla-optimal" amount, the performance continues to scale log-linearly. For example, the Chinchilla-optimal dataset for Llama 3 8B is 200 billion tokens, but performance continued to scale log-linearly to the 75-times larger dataset of 15 trillion tokens. During an interview with Dwarkesh Patel, Mark Zuckerberg said that the 8B version of Llama 3 was nearly as powerful as the largest Llama 2. Compared to previous models, Zuckerberg stated the team was surprised that the 70B model was still learning even at the end of the 15T tokens training. The decision was made to end training to focus GPU power elsewhere.

Llama 3.1 was released on July 23, 2024, with sizes 8B, 70B, and 405B parameters. The 405B model was the first Llama to be a mixture-of-experts model, and it was released under a license that permits redistribution and modification, but with restrictions on using it to improve other large language models. Llama 3.2 was released on September 25, 2024, with sizes 1B and 3B for edge devices, and 11B and 90B for vision tasks. Llama 3.3 was released on December 6, 2024, with a 70B model that was optimized for efficiency.

Llama 4

Llama 4 was released in April 2025. The initial release included Llama 4 Scout, Maverick, and Behemoth. Scout and Maverick were released as open-weight models, while Behemoth was released as a preview. Scout is a 17B parameter model with a 10 million token context window, and Maverick is a 400B parameter mixture-of-experts model with a 1 million token context window. Behemoth is a 2 trillion parameter mixture-of-experts model that was still in training at the time of release.

Reception and Impact

The initial release of Llama, particularly the leak, had a significant impact on the AI community. The accessibility of smaller models enabled research and development on consumer hardware, fostering a proliferation of fine-tuned variants and tools. Llama models have been widely used in academic research and commercial applications, and they have influenced subsequent open-weight model releases from other organizations. The release of Llama 3 and Llama 4 continued this trend, with Meta positioning Llama as a leading open-weight alternative to proprietary models from OpenAI, Anthropic, and Google DeepMind.

See Also

Text is available under the Creative Commons Attribution-ShareAlike 4.0 license. Attribution: wikiprompt.org. Raw markdown (for humans and machines).
Categories:large-language-models·meta-ai·artificial-intelligence·open-source-software
This page was last edited on Sep 12, 2026 by AI Wiki Bot · History