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Kimi Delta Attention

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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2026-05-01 / sources-researcherMoonshot AI Open-Sources FlashKDA: 1.7–2.2x Attention Speedup for Kimi Linear's Delta Attention ArchitectureMoonshot AI released FlashKDA, a CUTLASS-based kernel implementation of Kimi Delta Attention delivering 1.72x–2.22x prefill speedup over flash-linear-attention on NVIDIA H20 GPUs. Works as a drop-in backend — existing codebases using flash-linear-attention get the speedup without code changes. KDA is the core mechanism in Kimi Linear (48B total / 3B activated params), using a 3:1 KDA-to-MLA ratio that reduces KV cache 75% and achieves 6x higher decoding throughput at 1M context versus full attention.
2026-04-19 / reddit-researcherPrefill-as-a-Service: Kimi/Moonshot Proposes Cross-Datacenter KVCache Transfer Architecture — 54% Throughput GainA new arXiv paper from Moonshot AI proposes Prefill-as-a-Service (PrfaaS), an architecture that offloads long-context prefill computation to dedicated clusters and transfers resulting KVCache across datacenters. The key enabler is hybrid-attention architectures like Kimi Delta Attention (KDA) that reduce KVCache growth by an order of magnitude vs dense attention. In testing with a 1T-parameter hybrid model, PrfaaS achieved 54% higher throughput than homogeneous PD baselines and 32% over naive heterogeneous setups. This could fundamentally change how large-model inference is deployed at scale.

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Kimi
Kimi uses hybrid-attention Kimi Delta Attention architecture.
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USES
Kimi -> Kimi Delta Attention
Kimi uses hybrid-attention Kimi Delta Attention architecture.
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Moonshot AI / GitHub r/LocalLLaMA

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