Frontier model prices keep rising for the smartest models
与大多数人认为AI成本会持续下降的预期相反,作者指出最先进的模型价格实际上在上涨,这颠覆了人们对AI技术成本必然下降的传统认知,暗示AI市场可能正在分化为高端和低端两个层级。
Frontier model prices keep rising for the smartest models
与大多数人认为AI成本会持续下降的预期相反,作者指出最先进的模型价格实际上在上涨,这颠覆了人们对AI技术成本必然下降的传统认知,暗示AI市场可能正在分化为高端和低端两个层级。
Every layer in the stack now has to price the same way the customer thinks : per result, not per token.
大多数人认为AI服务的定价将继续基于token使用量等技术指标,但作者认为整个行业将转向基于结果的定价模式。这与当前AI API定价的主流实践相悖,暗示一场定价范式的革命即将到来。
Every layer in the stack now has to price the same way the customer thinks : per result, not per token.
大多数人认为AI服务应该按使用量(如token)计价,但作者认为整个AI堆栈都应该转向按结果计价。这挑战了当前AI API按token计费的主流模式,暗示行业将彻底改变定价策略,从技术指标转向业务价值。
Every layer in the stack now has to price the same way the customer thinks : per result, not per token.
大多数人认为AI服务应该按token使用量计费,这是行业标准做法,但作者认为未来所有层级都将转向按结果计价。这一观点挑战了当前AI定价的基础模式,暗示了整个AI价值链将从技术计量转向结果计量的根本转变。
a strong premium perception can sustain prices 10 to 20 percent above direct competitors without materially increasing churn or creating friction in the purchasing process.
令人惊讶的是:企业对AI产品的溢价感知能力比想象中更强,产品可以比直接竞争对手高出10-20%的价格而不显著增加客户流失率。这一发现挑战了传统定价理论,表明在AI领域,品牌价值和产品差异化可能比价格本身更能影响企业采购决策。
Codex-only seats have no rate limits, and usage is billed on token consumption.
大多数人认为AI服务通常会设置使用限制以控制成本,但作者认为Codex无速率限制的按token计费模式是可行的,因为这提供了更透明的成本结构和更灵活的使用体验,这可能反映了OpenAI对自身技术效率和用户需求的信心。
It turns out tools like Claude Code and Codex CLI can burn through enormous amounts of tokens once you start setting them more challenging tasks, to the point that $200/month offers a substantial discount.
running claudecode uses quite a bit of tokens, making 200usd/month a good deal for heavy users. I can believe that, also bc the machine doesn't care about the amount of tokens it uses during 'reasoning'. Some things I tried, it went through a whole bunch of steps and pages of scrolling output texts, to end up removing one word from a file. My suspicious half thinks, that if an AI company can influence the amount of tokens you use vibecoding, it will.