A reading roadmap traces the research stack behind Moonshot’s Kimi K3
East-Muffin-6472 · reddit · 2026-07-29
A detailed reading list maps the research lineage behind Kimi K3 and explains why the model is not an isolated release.
- It starts with Linear Transformers Are Secretly Fast Weight Programmers, which reframes linear attention as associative memory updates.
- Then it moves to Gated DeltaNet (2412.06464), where learned state updates improve long-sequence memory.
- Next is Kimi Linear / Kimi Delta Attention (KDA), described as Moonshot AI’s backbone architecture for Kimi K3.
- The post then covers LatentMoE → Stable LatentMoE, noting K3 activates 16 of 896 routed experts per token.
- It also highlights Attention Residuals (2603.15031) as a new way to let each layer selectively attend to previous layers.
- Finally, it recommends reading the Kimi model reports in order: K1.5 → K2 → K2.5 → K3 to see how reinforcement learning, multimodality, agentic behavior, and infrastructure improvements converged.
Related event: Kimi K3 Open-Source Model Architecture: Dropping RoPE for KDA and LatentMoE(5 posts)→
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