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English(EN) ⚖️ Open-weight DeepSeek V4 Pro 0423 scores 42.1 vs Claude Fable 5.1's 56.8 — a 14.7-point gap, but DeepSeek is 26x cheaper per 1M output tokens. That price diff

DeepSeek V4 Pro 尽管与 Claude Fable 5.1 存在性能差距,但提供了显著的成本节约

开放权重模型 DeepSeek V4 Pro 0423 的得分为 42.1,而 Claude Fable 5.1 的得分为 56.8,表明存在 14.7 分的性能差距。然而,DeepSeek V4 Pro 的成本效益要高得多,每百万输出 token 的价格便宜 26 倍。这种显著的价格差异改变了对基准测试结果的解读,暗示了原始性能与经济效率之间的权衡。 AI

影响 强调了模型性能与成本之间的权衡,影响了 AI 应用的采用决策。

排序理由 该项目报告了 AI 模型的基准测试分数,属于研究范畴。[lever_c 降级自研究:ic=1 ai=1.0]

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

DeepSeek V4 Pro 尽管与 Claude Fable 5.1 存在性能差距,但提供了显著的成本节约

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该项目报告了 AI 模型的基准测试分数,属于研究范畴。[lever_c 降级自研究:ic=1 ai=1.0]
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报道来源 [1]

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

    ⚖️ 开放权重DeepSeek V4 Pro 0423得分42.1,而Claude Fable 5.1得分为56.8——差距14.7分,但DeepSeek每100万输出令牌的价格便宜26倍。这个价格差异

    ⚖️ Open-weight DeepSeek V4 Pro 0423 scores 42.1 vs Claude Fable 5.1's 56.8 — a 14.7-point gap, but DeepSeek is 26x cheaper per 1M output tokens. That price difference changes what the benchmark gap means. https:// olud.ai/leaderboard.html # OpenSource # AI # LLM