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# Meta Releases Llama 3 in 8B and 70B Models, Trained on More Than 15 Trillion Tokens as Meta AI Expands Across Apps
- URL: https://www.theamericanquorum.com/taq-historical-2024-04-20-tech/
- Published: 2024-04-21T03:59:00.000Z
- Updated: 2024-04-21T03:59:00.000Z
- Description: Meta released Llama 3 in 8-billion- and 70-billion-parameter versions and began deploying the models through Meta AI and major cloud and developer platforms.
- Author: Kenneth R. Deans Jr.
- Tags: Tech, #Import 2026-09-01 13:54

Meta on Thursday released the first models in its Llama 3 family, introducing 8-billion- and 70-billion-parameter versions trained on more than 15 trillion tokens and immediately placing them into one of the technology industry’s fastest-moving competitions: the race to make increasingly capable generative artificial intelligence broadly available to developers and consumers. Meta’s [technical announcement](https://ai.meta.com/blog/meta-llama-3/?ref=theamericanquorum.com) says the two initial models are available in pretrained and instruction-tuned forms, while a much larger model with more than 400 billion parameters remains in training.

The release is consequential because Meta is pursuing two distribution paths at once. It is making Llama 3 available to developers under the company’s community license while also using it to power a more capable Meta AI assistant across Facebook, Instagram, WhatsApp, Messenger and a standalone web experience. Meta’s [April 18 rollout announcement](https://about.fb.com/ltam/news/2024/04/conoce-mas-sobre-meta-ai-creado-con-llama-3/?ref=theamericanquorum.com) says the assistant is expanding beyond the United States to more than a dozen countries, bringing Llama 3 into consumer products with billions of existing users.

## Two model sizes, one much larger training set

The initial Llama 3 release consists of 8B and 70B models, each offered in base and instruction-tuned variants. The official [8B model card](https://huggingface.co/meta-llama/Meta-Llama-3-8B?ref=theamericanquorum.com) describes an autoregressive transformer trained on a new mixture of publicly available online data, with an 8,000-token context length and more than 15 trillion pretraining tokens. The [70B instruction model](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct?ref=theamericanquorum.com) uses the same broad architecture, with supervised fine-tuning and reinforcement learning from human feedback applied to the tuned version.

Meta says the pretraining corpus is more than seven times larger than the one used for Llama 2 and includes four times more code. The company also introduced a tokenizer with a 128,000-token vocabulary intended to encode language more efficiently, and it trained the models on two custom-built 24,000-GPU clusters. Those engineering choices matter because model quality depends not only on parameter count but also on the volume and composition of training data, tokenization, post-training methods and the infrastructure available to run large experiments.

Independent distribution partners moved quickly. Hugging Face’s contemporaneous [launch note](https://huggingface.co/blog/llama3?ref=theamericanquorum.com) says all four primary variants — two base models and two instruction-tuned models — were available through its model hub on release day, along with Llama Guard 2\. Amazon Web Services likewise made Llama 3 available through SageMaker JumpStart on April 18, with an [AWS announcement](https://aws.amazon.com/about-aws/whats-new/2024/04/meta-llama-3-foundation-models-aws/?ref=theamericanquorum.com) listing initial availability in U.S., European and Asian regions.

## Meta turns its AI assistant into a distribution engine

The consumer strategy may be as important as the model release itself. Meta AI is being woven directly into search boxes, chats and feeds across the company’s largest applications. Users can invoke the assistant without leaving WhatsApp or Messenger, ask questions while browsing Facebook or Instagram, and generate images through Meta’s Imagine feature. The company is also launching a web destination for Meta AI, giving it a direct interface more comparable to standalone assistants from other AI companies.

That distribution gives Meta an unusual advantage: it does not need to persuade users to install a new application before exposing them to the model. Instead, Llama 3 can arrive inside services people already use. Meta says the assistant will provide real-time information from the web and will be available initially in English across markets including Australia, Canada, Ghana, Jamaica, Malawi, New Zealand, Nigeria, Pakistan, Singapore, South Africa, Uganda, Zambia and Zimbabwe.

The approach also creates a feedback loop between Meta’s developer and consumer strategies. Developers can adapt the underlying models for their own applications, while Meta can operate the same model family at enormous consumer scale. That contrasts with a purely proprietary model strategy in which access is limited primarily to a vendor’s own application or API.

## Safety tooling becomes part of the release package

Meta is pairing the new models with additional safety tools. Its [responsible-release description](https://about.fb.com/br/news/2024/04/nossa-abordagem-responsavel-para-o-meta-ia-e-o-meta-llama-3/?ref=theamericanquorum.com) details steps taken before launch and emphasizes developer resources intended to reduce unsafe uses. The Llama 3 technical release introduces Llama Guard 2, Code Shield and CyberSec Eval 2, tools aimed respectively at classifying unsafe content, identifying insecure code and evaluating cybersecurity risks.

The company’s model cards also describe limitations that developers must account for. The April release is primarily designed for English-language text, and the models have fixed knowledge cutoffs — March 2023 for the 8B version and December 2023 for the 70B version. Like other large language models, they can produce incorrect or misleading outputs, and downstream developers remain responsible for testing behavior in the specific environments where they deploy them.

The licensing model is broad but not unrestricted. Meta’s Llama 3 community license permits commercial and research use under specified conditions, while imposing additional requirements on very large platforms and prohibiting uses that violate the company’s acceptable-use policy. That structure continues Meta’s effort to position Llama as widely accessible without placing the weights in the public domain.

## The competitive question shifts from access to performance

Meta’s immediate claim is that the instruction-tuned versions are competitive with leading openly available models on common benchmarks for reasoning, coding and instruction following. Benchmark results are useful but incomplete indicators of real-world performance, especially because practical systems depend on retrieval, prompting, fine-tuning, latency, cost and safety controls as well as model scores.

Still, the combination of model availability and distribution changes the competitive landscape. Developers can download or deploy Llama 3 through multiple infrastructure providers rather than depend on a single hosted API. AWS’s same-day SageMaker support and Hugging Face’s launch integration reduce the operational work required to test the models. Meta says additional availability is planned through Microsoft Azure, Google Cloud, Databricks, IBM watsonx, NVIDIA NIM, Snowflake and other partners.

The larger question is what follows the 8B and 70B release. Meta says a model exceeding 400 billion parameters is still being trained and that the first Llama 3 release is only the beginning of the family. As of Saturday, the measurable development is already substantial: Meta has released two new model sizes, opened them to a broad developer ecosystem and simultaneously placed Llama 3 behind an AI assistant embedded across its consumer platforms. The next stage will test whether that combination of open distribution, large-scale deployment and rapid model iteration can translate into a durable advantage in generative AI.