The video provides an in-depth review of the newly released GPT-5.2 model, highlighting both its impressive advancements and notable regressions. While GPT-5.2 excels in code generation, tool calls, and benchmarks like ARC AGI, it surprisingly shows a significant regression in three-dimensional spatial reasoning, as demonstrated by its poor performance on a skateboard trick naming benchmark. This regression is puzzling given the model’s overall improvements, and the reviewer suggests that changes in default reasoning settings might have contributed to the lower scores. Despite this, GPT-5.2 performs exceptionally well on many other benchmarks, including GDP Val, SWEBench Pro, and math problem-solving without tools, showcasing its strength in knowledge work and reasoning tasks.

One of the standout features of GPT-5.2 is its enhanced instruction-following ability. Compared to other models like Opus and Composer, GPT-5.2 reliably executes tasks exactly as instructed, often delivering correct results on the first attempt. However, this precision comes at the cost of speed, with some tasks taking several minutes or even up to 30-50 minutes to complete, especially in the Pro and extra high reasoning modes. This slow response time is a significant downside, but the trade-off is a model that is more autonomous, careful, and capable of handling complex coding and reasoning tasks with less manual intervention.

The video also touches on GPT-5.2’s improvements in design and frontend capabilities, noting that the model generates high-quality UI components with consistent use of gradients and grid patterns. While GPT-5.2 claims better 3D visualization skills, the reviewer and some users have observed a regression in true 3D spatial understanding, possibly due to an overemphasis on 2D spatial reasoning. Despite this, the model produces visually appealing 3D-related outputs and is considered solid for frontend development tasks. Additionally, GPT-5.2 shows significant progress in reducing hallucinations, handling long context reasoning, and tool calling accuracy, making it more reliable for professional use.

Pricing for GPT-5.2 has increased compared to previous versions, reflecting its enhanced capabilities and token efficiency. Although the cost per token is higher, the overall cost to achieve a given quality level is lower due to better token utilization. The Pro version, however, is notably expensive, which may limit its accessibility. The model’s ability to handle extremely long contexts—up to 256k tokens with high accuracy—is a remarkable achievement, setting it apart from competitors like Grock 4. The video also highlights ongoing improvements in mental health considerations and the model’s ability to infer missing context, which enhances its usefulness in complex tasks.

In conclusion, GPT-5.2 represents a meaningful step forward in AI model development, particularly in instruction following, code generation, and reasoning. While it has some weaknesses, such as slower speeds and regressions in specific spatial reasoning tasks, its overall performance and reliability make it a powerful tool for professionals. The reviewer and other early testers praise its capabilities, especially in deep thinking and coding, though they caution that patience is required due to its slower processing times. The video encourages viewers to explore GPT-5.2 themselves and share their experiences, acknowledging that while it may not be perfect, it is currently one of the best models available.