llama3

What is LLaMa 3 and How It Differs from LLaMa 2

Souvik Datta

• 2 min read
What is LLaMa 3 and How It Differs from LLaMa 2

What is LLaMa 3 and How It Differs from LLaMa 2

The world of large language models (LLMs) is constantly evolving, with new advancements pushing the boundaries of what's possible. Meta's recent release of LLaMa 3 has sparked significant interest, particularly compared to its predecessor, LLaMa 2. 

This blog post dives into the details of LLaMa 3, exploring its key features and how it stands apart from LLaMa 2.

What is LLaMa 3?

LLama 3 is Meta's latest LLM, boasting significant improvements over its previous iteration. It's designed to excel in understanding the subtleties of language, grasping context effectively, and tackling complex tasks like translation and dialogue generation.

Key Strengths of LLaMa 3:

LLaMa 3 boasts better performance across all parameters compared to LLaMa 2. Here’s the comparison:

  • Enhanced Performance: LLaMa 3 tackles multi-step tasks effortlessly, thanks to refined post-training processes that minimize false rejections, improve response alignment, and generate more diverse answers.
  • Reasoning and Code Proficiency: This version demonstrates a stronger ability to reason and follow instructions, even incorporating code generation for various applications.
  • Amplified Context Window: While LLaMa 2 handled a context length of 4K tokens, LLaMa 3 doubled that capacity, allowing it to consider a broader range of information when responding.
  • Accessibility: Meta offers LLaMa 3 in two sizes (8B and 70B) for various deployment scenarios. The models are available on major cloud platforms like AWS, Google Cloud, and Azure, making them readily accessible to a wider audience.

LLama 3 vs. LLaMa 2: A Head-to-Head Comparison

Here's a breakdown of the key differences between LLaMa 3 and LLama 2:

Feature

LLaMa 2

LLaMa 3

Training Data Size

2 trillion tokens

15 trillion tokens (7x larger)

Context Window

4K tokens

8k tokens

Focus Area

General language understanding

Nuance, context, complex tasks

False Refusal Rate

Higher

Lower

Response Diversity

Lower

Higher

Code Generation

Limited capability

Enhanced capability

The Road Ahead for LLaMa

Meta isn't stopping here. They've promised a research paper delving deeper into LLaMa 3's technical aspects.

Additionally, they plan to introduce new functionalities, extend context windows further, and release more model sizes in the coming months. This continuous development suggests LLaMa is poised to make significant waves in the LLM landscape.

Conclusion

LLama 3 marks a significant leap forward in LLM technology. Its focus on understanding language nuances, handling complex tasks, and improving accessibility positions it as a strong contender in the field. With ongoing development, LLaMa 3 holds the potential to revolutionize various applications that rely on natural language processing.