研究显示 AI 达到同等基准性能的成本每年下降约 13 倍
AI performance costs are falling faster than those of any previous technology
Epoch 算出同性能成本一年降 13 倍，MIT 拆出算法本身贡献约 3 倍，但推理模型反而更烧钱，选型逻辑讲得挺清楚。
Epoch AI 的测算显示，AI 达到固定基准性能水平的价格每年下降约 13 倍，速度快于以往任何技术。MIT 研究在剔除硬件进步和竞争因素后，把算法层面的年度进步定在约 3 倍。
价格下降不等于最强模型更便宜，推理模型每个任务消耗的算力更多，成本可能反而更高。实际选模型时，质量、速度和错误率与价格同样重要。
AI performance costs are falling faster than those of any previous technology
AI is hitting a fixed benchmark performance level at a rapidly falling cost. Epoch AI measures a price decline of about 13x per year. After stripping out hardware gains and competition, MIT puts annual algorithmic progress at about 3x. That doesn't mean today's best models are cheaper, though. Reasoning models, for example, can cost more because they use far more compute per task. When picking a model for real-world use, quality, speed, and error rate matter just as much as price. The article AI performance costs are falling faster than those of any previous technology appeared first on The Decoder .
This report is categorized under AITOP's "Papers" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows and US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include Epoch AI, MIT, 推理模型, 基准测试.
Source attribution: curated from Decoder (@Alan Truly). Cross-source corroboration: 5 independent sources have covered this development (including Epoch AI, AI Will, Thomas Wolf), confirming industry-wide signal strength.
