OpenAI CEO Sam Altman stated that the company has not yet achieved AGI, but expects to have an internal system by the end of this year that he would be willing to call AGI; this statement refers to internal capabilities and does not commit to a public AGI product.

OpenAI's charter defines AGI as a highly autonomous system that outperforms humans in most economically valuable work. This definition does not have a unified external testing threshold, and whether AGI is achieved mainly depends on OpenAI's own judgment of the system's autonomy, coverage, and performance.

OpenAI's Chief Research Officer Mark Chen estimates that the company is about 80% away from AGI. Co-founder Greg Brockman stated that looking back from two years later, the current period may be seen as the starting point for the birth of AGI; neither announced that existing public models have reached this standard.

Altman also expects that the next generation of key models may "invent new things" in a way that has actual value for the first time. If this judgment holds, it means that the model's capability goals are shifting from answering, programming, and task execution to being research-oriented systems capable of proposing and validating new scientific, engineering, or business discoveries; however, OpenAI has not disclosed the architecture, training scale, benchmark scores, or validation standards of this internal system.

The term "internal system" suggests that OpenAI may first deploy more powerful models in a controlled environment for research, code development, model improvement, or other internal workflows. This allows for testing reliability, abuse risks, costs, tool invocation capabilities, and safety controls before large-scale external release, but it does not indicate when it will provide equivalent capabilities to ChatGPT, APIs, or enterprise customers.

Market mechanisms suggest that AGI expectations will increase capital investment in computing power, data centers, electricity, chips, model development talent, and AI applications. OpenAI and its computing partners may benefit from stronger product and financing bargaining power brought by more powerful models; application companies relying on existing capability gaps face pressure from the native functionality of models sinking. The true determinant of commercial impact is not the "AGI" label, but whether the system can complete high-value tasks that can replace human labor in a controllable cost, stability, and compliant manner.

Source: Public Information