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English(EN) Open weights do not mean easy deployment LongCat-2.5 activates about 48 billion parameters per token, but hosting a 1.6-trillion-parameter model still brings me

LongCat-2.5 模型部署面临严峻资源挑战

LongCat-2.5 模型拥有约 480 亿参数/token,但其 1.6 万亿参数的规模带来了显著的部署挑战。托管如此庞大的模型需要大量的内存、网络和加速器资源。对 LongCat-2.5 的独立测试有限,一些报告指出存在诸如编码任务失败并进入循环等问题。 AI

影响 LongCat-2.5 的庞大参数量凸显了高效部署先进 AI 模型所面临的持续挑战,需要大量的基础设施投资。

排序理由 该条目讨论了一个特定的 AI 模型及其技术特性和部署挑战,符合研究类别。[lever_c_demoted from research: ic=1 ai=1.0]

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LongCat-2.5 模型部署面临严峻资源挑战

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该条目讨论了一个特定的 AI 模型及其技术特性和部署挑战,符合研究类别。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

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

    开放权重不代表易于部署 LongCat-2.5 每个 token 激活约 480 亿参数,但托管一个拥有 1.6 万亿参数的模型仍然让我

    Open weights do not mean easy deployment LongCat-2.5 activates about 48 billion parameters per token, but hosting a 1.6-trillion-parameter model still brings memory, networking and accelerator demands. Independent testing remains limited, including one report of a failed, looping…