English(EN) Gemini 1.5 Pro's per-token price doubled past 128K tokens, so check the cost before you scale.

Google 将 Gemini 1.5 Pro 超过 128K token 的提示价格翻倍

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-05 19:30

Google 已将其 Gemini 1.5 Pro 模型在提示超过 128,000 token 后的每 token 价格翻倍。此次价格上涨使得 Gemini 1.5 Pro 在处理长提示时比之前更昂贵，尽管对于短提示而言，其成本效益仍与 OpenAI 的 GPT-4o 和 Anthropic 的 Claude 3.5 Sonnet 等模型具有竞争力。然而，Gemini 1.5 Pro 的独立质量基准有限，其 BenchLM 分数仅为估算，且缺乏与其他模型的直接比较。 AI

影响此次价格调整可能会影响利用长上下文窗口的应用程序的成本模型，对于非常大的提示可能会有利于竞争对手。

排序理由现有模型的定价变更，并非新发布或重大的行业转变。

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Google 将 Gemini 1.5 Pro 超过 128K token 的提示价格翻倍

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Signal score: 22 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 现有模型的定价变更，并非新发布或重大的行业转变。
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: product, infra; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

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dev.to — LLM tag TIER_1 English(EN) · Manohar Papasani · 2026-11-05 19:30

Gemini 1.5 Pro's per-token price doubled past 128K tokens, so check the cost before you scale.

Its input price was half of GPT-4o's, but BenchLM's quality score for it is only an estimate. Sources: BenchLM, Activepieces and Puter pricing breakdowns. Quality evidence is thin, so this post covers cost and limits. <ul> <li>What does a long prompt really co…

本文如何被排名

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Gemini 1.5 Pro's per-token price doubled past 128K tokens, so check the cost before you scale.

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