LLaMA vs GPT-4

Meta AI introduces LLaMA, an innovative 65-billion-parameter foundational language model, breaking new ground in the realm of language processing. Designed with efficiency in mind, LLaMA stands out for its remarkable performance despite a lower demand for computing resources. This groundbreaking model is presented in multiple sizes, catering to various research needs and allowing for extensive fine-tuning and application across a multitude of tasks. The emphasis on responsible AI practices is commendable, ensuring that the model adheres to ethical standards while aiding research across the globe. LLaMA brings with it the promise of advancing AI technology while mitigating challenges such as bias and toxicity commonly encountered in large language models.

GPT-4 is the latest milestone in OpenAI’s effort in scaling up deep learning.

GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks. For example, it passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5’s score was around the bottom 10%. We’ve spent 6 months iteratively aligning GPT-4 using lessons from our adversarial testing program as well as ChatGPT, resulting in our best-ever results (though far from perfect) on factuality, steerability, and refusing to go outside of guardrails.

GPT-4 is more creative and collaborative than ever before. It can generate, edit, and iterate with users on creative and technical writing tasks, such as composing songs, writing screenplays, or learning a user’s writing style.