OpenAI launches GPT 5.2 with advanced capabilities, to compete with Google’s Gemini 3

ChatGPT-maker OpenAI has launched GPT-5.2 artificial intelligence model, days after CEO Sam Altman issued an internal "code red" pausing internal projects and redirecting teams to accelerate development.

This comes as a response to Google's Gemini 3 that was launched last month. Announcing the new model, OpenAI said “We designed GPT‑5.2 to unlock even more economic value for people; it’s better at creating spreadsheets, building presentations, writing code, perceiving images, understanding long contexts, using tools, and handling complex, multi-step projects.”As revealed by the company, the new models is aimed to bring more economic value for users. “GPT‑5.2 Thinking sets a new state-of-the-art score, and is our first model that performs at or above a human expert level. Specifically, GPT‑5.2 Thinking beats or ties top industry professionals on 70.9% of comparisons on GDPval knowledge work tasks, according to expert human judges. These tasks include making presentations, spreadsheets, and other artifacts,” the company said.

Coding with GPT 5.2

OpenAI says that GPT‑5.2 Thinking sets a new state of the art of 55.6% on SWE-Bench Pro, a rigorous evaluation of real-world software engineering.

Unlike SWE-bench Verified, which only tests Python, SWE-Bench Pro tests four languages and aims to be more contamination-resistant, challenging, diverse, and industrially relevant.On SWE-bench Verified (not plotted), GPT‑5.2 Thinking scored 80%, as claimed by the AI maker. “For everyday professional use, this translates into a model that can more reliably debug production code, implement feature requests, refactor large codebases, and ship fixes end-to-end with less manual intervention,” it said.OpenAI further claims GPT‑5.2 Thinking hallucinates less than GPT‑5.1 Thinking. On a set of de-identified queries from ChatGPT, responses with errors were 30%rel less common. For professionals, this means fewer mistakes when using the model for research, writing, analysis, and decision support—making the model more dependable for everyday knowledge work.