English(EN) Our research on 29 AI coding models shows price per token predicts the wrong bill

研究发现，AI编码模型的Token定价错误地估计了成本

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-01 09:35

一项对29个AI编码模型进行分析的研究发现，按每分钟Token计费是一种估算成本的不准确方法。运行这些模型的实际成本与其在代理编码任务中的行为更密切相关，而不是其每Token费率。该研究对1,740次此类运行进行了评级和定价，以确定这种相关性。 AI

影响 AI编码模型的基于Token的定价可能无法准确反映实际使用成本，需要转向基于行为的成本分析。

排序理由研究论文分析AI编码模型。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 研究论文分析AI编码模型。[lever_c_demoted from research: ic=1 ai=1.0]
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Topics: product, other; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
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完整方法见我们的编辑标准。

Medium — AI coding tag TIER_1 English(EN) · Anand Das · 2026-10-01 09:35

我们对29款AI编码模型的调研显示，每token价格会预测错误的账单

<div class="medium-feed-item"><p class="medium-feed-snippet">We graded and priced 1,740 agentic coding runs. The bill followed how each model behaved. Some models that looked expensive on the rate…</p><p class="medium-feed-link"><a href="https://medium.com/@Anandbito/our-r…