OpenAI和Anthropic两大硅谷AI巨头近期大幅下调旗舰模型价格，引发业界价格竞争升级。[1]Anthropic于7月24日推出Claude Opus 5，定价为每百万Token输入5美元、输出25美元，较其前代产品Fable 5（输入10美元、输出50美元）降低50%。[1]随后OpenAI发布GPT-5.6，输入价格同样降至每百万Token 5美元，输出价格为30美元，亦为Fable 5价格的一半。[1]
这场价格竞争反映出市场需求的深刻变化。[1]企业用户的采购决策已从单纯追求性能指标转向关注单位任务成本，同时来自中国大模型的竞争压力也不容忽视。[1]数据显示，Kimi K3的定价为输入每百万Token约3美元、输出约15美元，价格更具竞争力。[1]与此同时，达到GPT-3.5水平的模型推理成本在2022年11月至2024年10月间下降了超过280倍，体现了技术进步对成本结构的深刻影响。[1]
尽管大幅降价，两家公司仍面临盈利压力。[1]OpenAI推理成本在2025年增长了四倍，导致调整后毛利率从40%降至33%，同时该公司将截至2030年的预计算力支出上调至近7500亿美元。[1]市场需求方面，企业用户的多模型采用趋势加剧竞争：37%的企业已同时使用五款以上模型，高于前一年的29%。[1]6月份Anthropic的企业付费采用率达到42.4%，OpenAI为39.5%。[1]此外，ChatGPT的周活跃用户已突破10亿，Codex和ChatGPT Work的活跃用户合计突破1000万。[1]
Leading artificial intelligence companies in Silicon Valley are engaged in aggressive pricing competition for their flagship large language models. Anthropic released Claude Opus 5 on July 24, pricing it at $5 per million tokens for input and $25 per million tokens for output—half the cost of its Fable 5 predecessor while maintaining comparable performance [1]. OpenAI subsequently launched GPT-5.6 with input pricing of just $5 per million tokens and output pricing of $30 per million tokens [1]. This pricing offensive reflects a fundamental shift in how enterprise customers evaluate AI services, with organizations increasingly prioritizing cost-effectiveness per task over raw performance metrics alone [1].
The competitive dynamics extend beyond these two companies, with pricing pressures originating partly from emerging rivals. Kimi K3 is available at approximately $3 per million tokens for input and $15 per million tokens for output [1]. Meanwhile, enterprise adoption patterns show fragmentation across vendors: 37% of enterprises now simultaneously use five or more AI models, up from 29% in the previous year [1]. By June, Anthropic had achieved a 42.4% enterprise paid adoption rate compared to OpenAI's 39.5% [1].
The pricing war reflects mounting cost pressures on AI providers. OpenAI's inference expenses quadrupled in 2025, compressing adjusted gross margins from 40% to 33% [1], while the company increased its projected computational spending through 2030 to nearly $750 billion [1]. However, the industry has achieved substantial efficiency gains: the inference cost to achieve GPT-3.5-level performance dropped by more than 280 times between November 2022 and October 2024 [1]. Despite competitive pressures on pricing, ChatGPT has reached over 1 billion weekly active users [1].
