1、GPT-4 Technical ReportOpenAIAbstractWe report the development of GPT-4,a large-scale,multimodal model which canaccept image and text inputs and produce text outputs.While less capable thanhumans in many real-world scenarios,GPT-4 exhibits human-level performanceon various professional and academic b

2、enchmarks,including passing a simulatedbar exam with a score around the top 10%of test takers.GPT-4 is a Transformer-based model pre-trained to predict the next token in a document.The post-trainingalignment process results in improved performance on measures of factuality andadherence to desired be

3、havior.A core component of this project was developinginfrastructure and optimization methods that behave predictably across a widerange of scales.This allowed us to accurately predict some aspects of GPT-4sperformance based on models trained with no more than 1/1,000th the compute ofGPT-4.1Introduc

4、tionThis technical report presents GPT-4,a large multimodal model capable of processing image andtext inputs and producing text outputs.Such models are an important area of study as they have thepotential to be used in a wide range of applications,such as dialogue systems,text summarization,and mach

5、ine translation.As such,they have been the subject of substantial interest and progress inrecent years 128.One of the main goals of developing such models is to improve their ability to understand and generatenatural language text,particularly in more complex and nuanced scenarios.To test its capabi

6、litiesin such scenarios,GPT-4 was evaluated on a variety of exams originally designed for humans.Inthese evaluations it performs quite well and often outscores the vast majority of human test takers.For example,on a simulated bar exam,GPT-4 achieves a score that falls in the top 10%of test takers.Th