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English(EN) DeepSeek-V4-Flash: The Open-Weight AI Model Pricing Inference at $0.08/M — Day 7/30

DeepSeek-V4-Flash发布，拥有百万级上下文窗口，定价低廉但速度不稳

作者 PulseAugur 编辑部 · [1 个来源] ·

DeepSeek-V4-Flash已发布，拥有超过一百万个token的超大上下文窗口，且定价极具竞争力，每百万输入token成本为0.078美元，每百万输出token成本为0.156美元。这使得它在处理大量文本的任务中具有经济可行性，例如总结大型代码库或法律文件。然而，性能测试显示其在推理任务上存在显著的延迟问题，表明虽然该模型在批量处理方面成本低廉，但其在复杂认知任务上的速度不一致，且远慢于其编码能力。 AI

影响 为大上下文LLM应用提供了新的经济基准，但用户必须仔细评估推理任务的延迟。

排序理由 Frontier-lab模型发布，系统卡片[lever_c_demoted from frontier_release: ic=1 ai=1.0]

在 dev.to — LLM tag 阅读 →

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

DeepSeek-V4-Flash发布，拥有百万级上下文窗口，定价低廉但速度不稳

本文如何被排名

Signal score
73 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Significant
Frontier-lab模型发布，系统卡片[lever_c_demoted from frontier_release: ic=1 ai=1.0]
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
model release, product
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。

报道来源 [1]

  1. dev.to — LLM tag TIER_1 English(EN) · AI Explore ·

    DeepSeek-V4-Flash：开放权重AI模型定价推理，每百万字符仅需0.08美元 — 第7/30天

    <blockquote> <p><strong>TL;DR —</strong> DeepSeek-V4-Flash pairs a 1,048,576-token context with $0.078/M input and $0.156/M output pricing, and my probes show it nailing code, math, and structured extraction. But its reasoning-task latency was wildly inconsistent — a real cost fo…

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