GPT-5为什么没有带来更多惊喜？

Core Insights - OpenAI has released its latest model, GPT-5, after a 29-month gap since GPT-4, but initial feedback has been mixed, with some users expressing disappointment over the perceived lack of significant improvements [1][5][39] - GPT-5's performance metrics do not show a substantial advantage over competitors like Grok 4 and Claude Opus 4.1, with some benchmarks indicating it falls short in certain areas [2][10][15] - Despite the criticisms, GPT-5 is positioned as a cost-effective model, with input costs significantly lower than its predecessors, making it one of the most comprehensive models available [18][19] Group 1: Model Performance and User Feedback - Users have reported dissatisfaction with GPT-5, feeling it does not offer enough upgrades compared to GPT-4o, leading OpenAI to reintroduce the older model for Plus users [3][59] - The release of GPT-5 has highlighted the limitations of scaling laws, suggesting that further increases in model size may not yield proportional performance gains [4][6] - In various benchmark tests, GPT-5 has been outperformed by other models, raising concerns about its competitive edge in the market [10][12][15] Group 2: Cost and Accessibility - GPT-5's input cost is $1.25 per million tokens, which is about half the cost of GPT-4o, while the nano version is as low as $0.05 per million tokens, enhancing its affordability [18][47] - OpenAI has emphasized the importance of practical applications and user accessibility, aiming to make advanced AI capabilities available to a broader audience [26][35] - The model's unified approach aims to simplify user experience by reducing the need for multiple model selections, although this has led to some confusion among users regarding which version they are interacting with [40][51] Group 3: Industry Impact and Adoption - GPT-5 has been quickly integrated into various Microsoft products and other applications, indicating a strong interest in its capabilities for business applications [25][26] - OpenAI's focus on industry-specific applications, particularly in programming, has been a significant aspect of the GPT-5 launch, with extensive demonstrations during the release event [23][24] - The model's design aims to enhance reliability and usability, addressing previous issues with hallucinations and user engagement [27][34]