Compare GPT-3.5 vs. GPT-4o mini vs. Phi-3

The GPT-3.5 series represents an advancement in OpenAI's large language models, building on the capabilities of its predecessor, GPT-3. These models excel at comprehending and producing human-like text, with four primary variations designed for various applications. The core GPT-3.5 models are intended to be utilized through the text completion endpoint, while additional models are optimized for different endpoint functionalities. Among these, the Davinci model family stands out as the most powerful, capable of executing any task that the other models can handle, often requiring less detailed input. For tasks that demand a deep understanding of context, such as tailoring summaries for specific audiences or generating creative content, the Davinci model tends to yield superior outcomes. However, this enhanced capability comes at a cost, as Davinci requires more computing resources, making it pricier for API usage and slower compared to its counterparts. Overall, the advancements in GPT-3.5 not only improve performance but also expand the range of potential applications.

A compact model that excels in textual understanding and multimodal reasoning capabilities. The GPT-4o mini is designed to handle a wide array of tasks efficiently, thanks to its low cost and minimal latency, making it ideal for applications that require chaining or parallelizing multiple model calls, such as invoking several APIs simultaneously, processing extensive context like entire codebases or conversation histories, and providing swift, real-time text interactions for customer support chatbots. Currently, the API for GPT-4o mini accommodates both text and visual inputs, with plans to introduce support for text, images, videos, and audio in future updates. This model boasts an impressive context window of 128K tokens and can generate up to 16K output tokens per request, while its knowledge base is current as of October 2023. Additionally, the enhanced tokenizer shared with GPT-4o has made it more efficient in processing non-English text, further broadening its usability for diverse applications. As a result, GPT-4o mini stands out as a versatile tool for developers and businesses alike.

Introducing a remarkable family of compact language models (SLMs) that deliver exceptional performance while being cost-effective and low in latency. These models are designed to enhance AI functionalities, decrease resource consumption, and promote budget-friendly generative AI applications across various platforms. They improve response times in real-time interactions, navigate autonomous systems, and support applications that demand low latency, all critical to user experience. Phi-3 can be deployed in cloud environments, edge computing, or directly on devices, offering unparalleled flexibility for deployment and operations. Developed in alignment with Microsoft AI principles—such as accountability, transparency, fairness, reliability, safety, privacy, security, and inclusiveness—these models ensure ethical AI usage. They also excel in offline environments where data privacy is essential or where internet connectivity is sparse. With an expanded context window, Phi-3 generates outputs that are more coherent, accurate, and contextually relevant, making it an ideal choice for various applications. Ultimately, deploying at the edge not only enhances speed but also ensures that users receive timely and effective responses.