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English(EN) Kimi K3's architecture activates only 16 of 896 available experts during inference, suggesting efficiency gains. Moonshot claims 2.5x better scaling versus K2.

Moonshot 的 Kimi K3 声称通过专家激活提高效率

作者 PulseAugur 编辑部 · [1 个来源] ·

据报道，Moonshot 的 Kimi K3 模型在推理时仅激活 896 个可用专家中的 16 个，这表明效率可能有所提高。该公司声称，与前代 K2 相比，这种新架构的扩展性提高了 2.5 倍。然而，由于尚未发布权重，目前无法对这些说法进行外部验证，预计将在 7 月 27 日左右发布更多信息。 AI

影响 更高效的 LLM 架构和改进的扩展性有可能加速在资源受限环境中的部署。

排序理由 Moonshot 的 Kimi K3 模型发布，附带系统卡。[lever_c_demoted from frontier_release: ic=1 ai=1.0]

在 Mastodon — sigmoid.social 阅读 →

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

Moonshot 的 Kimi K3 声称通过专家激活提高效率

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Significant
Moonshot 的 Kimi K3 模型发布，附带系统卡。[lever_c_demoted from frontier_release: ic=1 ai=1.0]
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报道来源 [1]

  1. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    Kimi K3 在推理时仅激活 896 个可用专家中的 16 个，表明效率有所提升。Moonshot 声称其扩展性是 K2 的 2.5 倍。

    Kimi K3's architecture activates only 16 of 896 available experts during inference, suggesting efficiency gains. Moonshot claims 2.5x better scaling versus K2. The catch: outside researchers cannot yet verify these claims without released weights. We'll know more July 27. https:/…

    链接 implicator.ai/moonshot-launches-kimi-k3-w…

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