As an AI language model, ChatGPT is a single model based on the GPT-3.5 architecture (latest GPT-4). However, there are multiple versions of ChatGPT that have been trained on different amounts of data and with different hyperparameters.
OpenAI currently offers access to several pre-trained versions of it with varying numbers of parameters and capabilities, including the following:
GPT-4 is an advanced language model that can process both text and image inputs and can generate human-like text outputs. While it may not be as capable as humans in certain real-world situations, it has been designed to perform at a level comparable to humans on various professional and academic assessments.
In simpler terms, GPT-4 is a highly sophisticated AI system that can understand and respond to both written and visual information and has been programmed to excel at certain tasks that are typically performed by professionals and academics.
GPT – 3.5 Model
GPT-3.5 is a family of AI models that have the ability to comprehend and produce natural language as well as computer code. Among the GPT-3.5 models, the most efficient and powerful one is the gpt-3.5-turbo model, which has been specifically designed and fine-tuned for chat applications.
However, it can also perform effectively in other tasks that involve generating responses or completing tasks, such as auto-completion of text.
In simpler terms, GPT-3.5 is a group of advanced AI models that are capable of understanding and creating human-like language and code, and gpt-3.5-turbo is the best option for chat-based applications, but it can also perform well in other similar tasks.
GPT-3 (175 billion parameters)
GPT-3 (175 billion parameters): This is the largest version of ChatGPT, with the most parameters and capabilities. It is trained on a massive corpus of text and can generate a wide variety of responses that are often indistinguishable from those written by humans.
It can perform a wide range of natural language processing (NLP) tasks, including language translation, summarization, question-answering, and text completion.
GPT-3 (13 billion parameters)
GPT-3 (13 billion parameters): This version of ChatGPT is smaller than the 175 billion-parameter version, but still very powerful. It is capable of generating high-quality text that is often very similar to that written by humans. It can perform many of the same NLP tasks as the larger version, but with somewhat less accuracy and variety.
GPT-2 (1.5 billion parameters)
GPT-2 (1.5 billion parameters): This version of ChatGPT was released before GPT-3 and is smaller and less powerful. However, It is still capable of generating high-quality text and can perform a range of NLP tasks, including text generation, text completion, and text classification.
GPT-2 (774 million parameters)
GPT-2 (774 million parameters): This is a smaller version of the 1.5 billion-parameter GPT-2 model. It has fewer parameters and capabilities than the larger version, but can still generate high-quality text and perform some NLP tasks.
GPT-2 (355 million parameters)
GPT-2 (355 million parameters): This is an even smaller version of the GPT-2 model, with fewer parameters and capabilities. But still capable of generating coherent text, but may struggle with more complex NLP tasks.
GPT-2 (117 million parameters)
GPT-2 (117 million parameters): This is the smallest version of the GPT-2 model, with the fewest parameters and capabilities. But still capable of generating coherent text, but may struggle with more complex NLP tasks and may have a more limited range of responses.
Each of these versions of ChatGPT has different strengths and weaknesses and can be used for different applications and tasks. For example, the larger versions (like GPT-3 and GPT-4) have more parameters and can generate more complex and diverse text, while the smaller versions (like GPT-2) may be more suitable for simpler tasks or applications where computational resources are limited.
Overall, the larger versions of ChatGPT have more parameters and capabilities and can generate more complex and diverse text, while the smaller versions are more lightweight and may be more suitable for simpler tasks or applications.