Long Context & Efficient Sequences · 2025

MoBA: Mixture of Block Attention for Long-Context LLMs

Enzhe Lu, Zhejun Jiang, Jingyuan Liu, et al. (Moonshot AI / Kimi)

Applies MoE-style routing to attention so each query attends to a learned subset of key-value blocks, allowing a model to switch between full and sparse attention and serve long context in production (Kimi).

Editorial record

Plain-language summary

Applies MoE-style routing to attention so each query attends to a learned subset of key-value blocks, allowing a model to switch between full and sparse attention and serve long context in production (Kimi).

Knowledge graph

Relationships

Descendants

  • Depends onEvidence: Strongly supported

    Attention Is All You Need

    Builds on the long context lineage in the archive

    freshness sweep 2026

Source record

Provenance

Record ID
P-607
Record created
2026-07-13
Last reviewed
2026-07-14
Record version
2

Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.