4 comments

  • delichon 5 minutes ago
    If you want to believe that the success of Kimi is about distillation attacks, ignore this.
  • senko 4 minutes ago
    Old but relevant: if you read the recently-released Kimi K3 paper[0], you'll see that it's heavily based on Kimi Linear discussed here, scaling it up and adding a bunch more things (like native vision and RL improvements).

    [0] https://arxiv.org/abs/2607.24653

  • jasonjmcghee 1 hour ago
    (2025)

    As it's 9 months old and they just had a major model release

    • throwa356262 51 minutes ago
      For K3 read this instead: https://arxiv.org/abs/2607.24653

      The main contribution of the K3 paper is Stable LatentMoE. Like some other models it compresses data sent between layers, which puts certain requirements on the router. K3 improves performance by using a more balanced expert selection strategy.

      • senko 3 minutes ago
        Not an expert, but looks like they did a lot more work on the RL part (9 expert models, full sandbox access for agentic tasks, etc)?
      • mcbuilder 34 minutes ago
        Compared to the Opus 5 "model card", which read like a standard Anthropic set of alignment principles and safety concerns, this presents a plethora of useful technical details that advances the state of the art.
        • throwa356262 30 minutes ago
          Same with DeepSeek papers, they are a joy to read.
    • cptcobalt 48 minutes ago
      Rather under-discussed back then: https://news.ycombinator.com/item?id=45766937
    • GaggiX 1 hour ago
      I believe OP posted it because the new Kimi K3 has 69 KDA layers (the rest are 24 Gated MLA), I think previous large Kimi models had only MLA layers.
      • yorwba 25 minutes ago
        It's not the same KDA as used in Kimi Linear, though.
        • GaggiX 23 minutes ago
          What's the difference? They are both called Kimi Delta Attention.
  • Topology1 19 minutes ago
    Another banger from Zhang et. al