Llama 3 is Meta AI’s latest large language model, launched in April 2024 with an update to version 3.1 in July 2024. While it remains focused on text-based outputs, it now supports coding, though it lacks the ability to generate images, video, or audio.

Llama 3 Models

Llama 3.1 offers three versions: 405B, 70B, and 8B, with the largest being the 405B model. It is trained on 405 billion parameters and has a 128,000-token context window, allowing it to handle larger datasets and maintain contextual awareness across longer inputs. This model is ideal for high-level research, synthetic data generation, and other large-scale tasks. It has undergone extensive pre-training and fine-tuning with trillions of tokens, and human feedback has improved its accuracy and safety features. However, due to its size, it is costly to run and requires advanced data center hardware.

The 70B model, trained on 70 billion parameters, is more compact and efficient than the 405B version. It maintains the same context window but is faster and cheaper to run, making it suitable for commercial applications, such as customer support chatbots. While it lacks the depth of the 405B model, it offers a good balance of performance and resource efficiency.

Llama 3.1’s 8B model, trained on eight billion parameters, is the leanest version. It retains the 128,000-token context window but has less training data, making it less accurate and capable than the larger models. However, its lightweight design allows it to run locally on consumer hardware, making it useful for developers who want to integrate AI features into smaller-scale projects.

Abilities of Llama 3

Llama 3’s models are highly capable and competitive with other top models, such as GPT-4. The 405B version performs exceptionally well in benchmarks, while the 70B and 8B models offer competitive alternatives for faster, leaner operations.

Llama 3 excels in coding support, helping users write their own code or generating simple programs. It supports over 30 languages, though it performs best in English. Additionally, it is effective for generating text across various writing tasks, including business, fiction, and social media content. Llama 3’s large context window allows for fine-tuned prompts and more nuanced responses.

A significant improvement in Llama 3 is its advanced safety features. It includes Llama Guard 3, a multi-lingual safety system, and Prompt Guard, which helps prevent malicious code injection. These safeguards, combined with its open-source nature, provide users with a versatile and secure platform for building AI-powered applications.

A major benefit of Llama 3 is its open-source status. This accessibility allows developers and users to customize and expand the model, encouraging innovation and accelerating the development of Llama 3-based tools and AI solutions.

Limitations

Despite its strengths, Llama 3 has some notable limitations. Although it is a multi-modal model, it currently lacks full multi-modal support, such as image, video, or audio generation. Its performance in languages other than English is still limited, and it suffers from occasional hallucinations, where the model confidently presents incorrect information, a common issue among large language models.

The 405B model is also expensive to run due to its size and the hardware requirements, which limits access to this powerful version. While the smaller models, like 70B and 8B, are more accessible, they lack the comprehensive capabilities of the 405B model.

Training Llama 3 was an expensive endeavor, requiring thousands of Nvidia H100 GPUs. Even Meta, with its vast resources, had to carefully manage the time and hardware used for training these models.

Llama 3 GitHub site --> https://github.com/meta-llama/llama3