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    DeepSeek vs. Kimi: A user argues that owning compute matters

    A user calls Moonshot too dependent on Alibaba and suggests that reusing an older model base—if that is what K2.8 does—could signal resource scarcity.

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    1 Source, 19d ago, first seen 19d ago

    TLDR

    Ownership of computing resources is central to one user's case for DeepSeek over Kimi. If K2.8 is a post-trained version of K2.7—ultimately tracing back to K2 from July 2025—they see that as a possible sign that Kimi is struggling to train new base models. In a follow-up, they say work on K3 reinforcement learning is underway but argue that Moonshot is too dependent on Alibaba.

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    1 Source, first seen 19d ago

    Combined views

    1.7K

    1 Source, first seen 19d ago

    22 likes
    22 likes
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    1 comments
    2 saves

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    1 Source

    @teortaxesTexof course, they are working on K3 RL. But if they felt the need to push an old MLA base (I hope they upgraded to DSA++ at least) one more time, that suggests non-funny scarcity issues. Moonshot is too dependent on Alibaba. Whale is dependent only on Liang's execution.

    1 Source

    @teortaxesTexof course, they are working on K3 RL. But if they felt the need to push an old MLA base (I hope they upgraded to DSA++ at least) one more time, that suggests non-funny scarcity issues. Moonshot is too dependent on Alibaba. Whale is dependent only on Liang's execution.