OpenAI releases GPT-5.2-Codex, which is deeply optimized for agent coding.

On December 19th, OpenAI officially released its next-generation code generation model, GPT-5.2-Codex, which is further optimized based on its advanced GPT-5.2 architecture.

In the announcement, co-founder Sam Altman stated that GPT-5.2-Codex is specifically designed for agent programming and edge application scenarios. After large-scale targeted training, it demonstrates significant capabilities in code generation, logical reasoning, and system-level task processing.

Altman revealed that the model has already been piloted internally at OpenAI, and employees have used it to significantly improve development efficiency and project completion quality, achieving "huge success."

This release is seen as an important step for OpenAI in deepening AI applications in vertical fields.

GPT-5.2-Codex not only supports multiple programming languages and complex instruction understanding but also enables efficient deployment in edge environments, potentially providing developers, enterprises, and research teams with a more powerful auxiliary programming tool.

Meanwhile, according to sources, OpenAI is planning a new round of large-scale financing, targeting a valuation of up to $830 billion, with expected fundraising not exceeding $100 billion.

If the funding round is successfully completed, it will be one of the largest and highest-valued funding events in the field of artificial intelligence to date, highlighting the market's strong confidence in OpenAI's technological potential and commercial prospects.

Under this strategic plan, OpenAI may further expand its investment in global AI infrastructure, enterprise solutions, and cutting-edge research.

With the launch of GPT-5.2-Codex and the progress of its massive funding plan, OpenAI is continuously consolidating its leading position in generative artificial intelligence, while also indicating that the commercialization and ecosystem building of AI technology are entering a new phase of acceleration. (Source: BlockBeats)