OpenAI新模型Day0就被嫌弃！排名拉垮，不如一月底发布的国产模型

Core Viewpoint - OpenAI's newly launched GPT-5.4 mini has received criticism for its performance and pricing, ranking 13th in the Vals benchmark, which is an improvement over the previous GPT-5 but still underwhelming compared to competitors [2][4][6]. Performance Comparison - The GPT-5.4 mini achieved a score of 57.88% in the Vals benchmark, while the previous GPT-5 scored 56.10%, indicating a slight improvement [2][5]. - In various performance tests, the mini and nano models showed significant enhancements, with the mini version performing close to the full GPT-5.4 in several benchmarks, such as SWE-Bench Pro and OSWorld-Verified [10][12][25]. Pricing Analysis - The pricing for GPT-5.4 mini is approximately three times higher than the previous GPT-5 mini, with costs of $0.75 per million input tokens and $4.50 per million output tokens [16][6]. - The nano version is significantly cheaper, costing $0.20 per million input tokens and $1.25 per million output tokens, making it a more economical choice for certain tasks [16][31]. Market Position - Despite the improvements, the mini and nano models are still considered average in the global landscape, ranking lower than models from competitors like Kimi and Qwen [4][19]. - Users have noted that the performance of the new models is not compelling enough to justify the price increase, with some suggesting that alternatives like Gemini Flash 3 lite offer better performance at a lower cost [17][19]. Use Cases - The GPT-5.4 mini and nano models are optimized for programming, computer operations, and multi-modal tasks, making them suitable for applications where low latency is critical [14][20][23]. - In practical applications, the mini model has shown to be effective in tasks such as code modification and debugging, while the nano model excels in simpler tasks like classification and data extraction [20][28][34].