MPT-30B vs GPT-4

MPT-30B sets a new standard in the world of open-source foundation models, delivering enhanced performance and innovation. Developed using NVIDIA H100 Tensor Core GPUs, this transformational model boasts an impressive 8k context length, allowing for a deeper and more nuanced understanding of text. As part of the acclaimed MosaicML Foundation Series, MPT-30B offers open-source access and a license for commercial use, distinguishing itself as a highly accessible and powerful tool. It comes with specialized variants, including Instruct and Chat, suited for different applications.

The model is optimized for efficient inference and training performance through technologies like ALiBi and FlashAttention, also featuring remarkable coding abilities thanks to its comprehensive pre-training data mixture. MPT-30B is strategically designed for single-GPU deployment, making it a convenient choice for a wide range of users.

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.