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English(EN) DeepSeek V3.2 dropped from $0.80 to $0.38 per 1M output tokens in 30 days — a 53% cut on open weights. If inference costs keep halving this fast, proprietary AP

DeepSeek V3.2 一个月内推理成本削减 53%

DeepSeek 已显著降低其 V3.2 模型的推理成本,在短短 30 天内将每 100 万输出 token 的价格从 0.80 美元降至 0.38 美元。开放权重模型 53% 的降幅表明 AI 推理费用正在迅速下降。如此快速的成本降低可能会挑战专有 AI API 的高价策略。 AI

影响 开放权重模型的推理成本快速下降可能会给专有 API 定价带来压力,并加速 AI 的采用。

排序理由 该条目详细说明了开放权重 AI 模型显著的成本降低,这是 AI 基础设施领域的一项研究相关进展。[lever_c_demoted from research: ic=1 ai=1.0]

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DeepSeek V3.2 一个月内推理成本削减 53%

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该条目详细说明了开放权重 AI 模型显著的成本降低,这是 AI 基础设施领域的一项研究相关进展。[lever_c_demoted from research: ic=1 ai=1.0]
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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
infra, model release
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报道来源 [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · opensourceaitech ·

    DeepSeek V3.2 在 30 天内从每 100 万输出 token 0.80 美元降至 0.38 美元 — 开放权重削减 53%。如果推理成本继续以如此快的速度翻倍,专有 AP

    DeepSeek V3.2 dropped from $0.80 to $0.38 per 1M output tokens in 30 days — a 53% cut on open weights. If inference costs keep halving this fast, proprietary APIs will have to justify every premium. https:// olud.ai/model/deepseek-v3-2.ht ml # AI # LLM # Pricing