Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving

Mooncake is the serving platform for Kimi, an LLM chatbot service developed by Moonshot AI. This platform features a KVCache-centric disaggregated architecture that not only separates prefill and decoding clusters but also efficiently utilizes the underexploited CPU, DRAM, SSD and NIC resources of the GPU cluster to establish a disaggregated KVCache. At the core of Mooncake is its KVCache-centric global cache and a scheduler designed to maximize throughput while adhering to stringent latency-related Service Level Objectives (SLOs). Our experiments demonstrate that Mooncake excels in scenarios involving long-context inputs. In tests using real traces, Mooncake increases the effective request capacity by 59% ∼ 498% when compared to baseline methods, all while complying with SLOs. Currently, Mooncake is operational across thousands of nodes, processing over 100 billion tokens daily. In practical deployments, Mooncake ’s innovative architecture enables Kimi to handle 115% and 107% more requests on NVIDIA A800 and H800 clusters, respectively, compared to previous systems.

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Publication Details

Journal
ACM Transactions on Storage
Published
2025-11-15
DOI
https://doi.org/10.1145/3773772
Primary Topic
Big Data and Digital Economy
Type
article
Field-Weighted Citation Impact
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article

Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving

Y X Zhang, Shangming Cai, Heyi Tang, Feng Ren et al.
ACM Transactions on Storage
Big Data and Digital Economy
article

Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving

Y X Zhang, Shangming Cai, Heyi Tang, Feng Ren, Zheming Li, Mingxing Zhang, Jialei Cui, Teng Ma, Ruoyu Qin, Weimin Zheng, Weiran He, Xinran Xu, Yongwei Wu
article en

Abstract

Mooncake is the serving platform for Kimi, an LLM chatbot service developed by Moonshot AI. This platform features a KVCache-centric disaggregated architecture that not only separates prefill and decoding clusters but also efficiently utilizes the underexploited CPU, DRAM, SSD and NIC resources of the GPU cluster to establish a disaggregated KVCache. At the core of Mooncake is its KVCache-centric global cache and a scheduler designed to maximize throughput while adhering to stringent latency-related Service Level Objectives (SLOs). Our experiments demonstrate that Mooncake excels in scenarios involving long-context inputs. In tests using real traces, Mooncake increases the effective request capacity by 59% ∼ 498% when compared to baseline methods, all while complying with SLOs. Currently, Mooncake is operational across thousands of nodes, processing over 100 billion tokens daily. In practical deployments, Mooncake ’s innovative architecture enables Kimi to handle 115% and 107% more requests on NVIDIA A800 and H800 clusters, respectively, compared to previous systems.

ACM Transactions on Storage
Health Decisions (United States) (US), Oldham Council (GB), Alibaba Group (China) (CN), Tsinghua University (CN)
Openalex Percentile: Top 52%
Big Data and Digital Economy
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