Key Highlights of GPT‑4: Multimodal Capabilities, Benchmark Performance, and Future Implications

GPT‑4, the highly anticipated multimodal model, accepts both image and text inputs and generates text, code, and other outputs, achieving human‑level performance on a wide range of professional and academic benchmarks.

It can solve SAT, GRE, and other standardized tests with top scores, outperform GPT‑3.5 in advanced reasoning tasks such as law‑school exams, and handle up to 32 K tokens, enabling long‑form content creation and analysis.

Notably, GPT‑4 can generate complete web page code from hand‑drawn sketches, describe multiple images, detect inconsistencies, and perform step‑by‑step reasoning on charts and exam questions.

OpenAI reports that GPT‑4’s improvements stem from extensive adversarial testing, a rebuilt deep‑learning stack, and a custom supercomputer built with Microsoft Azure, leading to greater reliability, controllability, and safety.

Despite its power, the model is still considered a “toy” in many respects, lacking a true knowledge base and sometimes producing fabricated answers, so careful deployment is advised.