Zipage: Maintain High Request Concurrency for LLM Reasoning through Compressed PagedAttention
On the map: LLM reasoning → Test-time compute and efficient thinking
Abstract (arXiv)
With reasoning becoming the generative paradigm for large language models (LLMs), the memory bottleneck caused by KV cache during the decoding phase has become a critical factor limiting high-concurrency service. Although existing KV cache eviction methods address the memory issue, most of them are impractical for industrial-grade applications. This paper introduces Compressed PagedAttention, a method that combines token-wise KV cache eviction with PagedAttention. We propose a comprehensive scheduling strategy and support prefix caching and asynchronous compression for Compressed PagedAttention. Based on this, we have developed a high-concurrency LLM inference engine, Zipage. On large-scale mathematical reasoning tasks, Zipage achieves around 95% of the performance of Full KV inference engines while delivering over 2.1× speedup.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in Test-time compute and efficient thinking, one of 17 directions in LLM reasoning. Builds on 16 of its 27 references that are in the map. First posted on arXiv 1 Mar 2026.
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16 of 27 references.
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Other references · 15
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- 2024PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funnelingcited by 432
- 2025From System 1 to System 2: A Survey of Reasoning Large Language Modelscited by 320
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- 2023SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefillscited by 193
- 2025A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systemscited by 111
- 2025Shared Global and Local Geometry of Language Model Embeddingscited by 36
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Citing papers per year: 2026: 4.
4 papers.
- 2026vToken: Token-Level Virtualization for Reclaimable KV Cachescited by 1
- 2026Keyless Attention: Value-Space Routing and Value-Only Caching for Efficient Transformerscited by 0
- 2026GrowPage: On-Demand KV Budgeting for Efficient LLM Reasoning Servingcited by 0
- 2026Does Execution Require Target KV Fidelity? A Mixed-Fidelity KV Runtime for LLM Servingcited by 0
- 2026Does Execution Require Target KV Fidelity? A Mixed-Fidelity KV Runtime for LLM Serving27 Sep 2026
- 2026GrowPage: On-Demand KV Budgeting for Efficient LLM Reasoning Serving3 Sep 2026
- 2026vToken: Token-Level Virtualization for Reclaimable KV Caches13 Aug 2026
- 2026Keyless Attention: Value-Space Routing and Value-Only Caching for Efficient Transformers20 Jun 2026
Similar, not cited
Close in wording, no citation either way
- 2026KARA: Efficient Reasoning LLM Serving via Sliding-Window KV Cache Compression
- 2026Fast KVzip: Efficient and Accurate LLM Inference with Gated KV Eviction
- 2026ArborKV: Structure-Aware KV Cache Management for Scaling Tree-based LLM Reasoning
- 2026RKSC: Reasoning-Aware KV Cache Sharing and Confident Early Exit for Multi-Step LLM Inference
- 2024Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference
- 2025HAMburger: Accelerating LLM Inference via Token Smashing
- 2026Not All Thoughts Need HBM: Semantics-Aware Memory Hierarchy for LLM Reasoning
- 2025LazyEviction: Lagged KV Eviction with Attention Pattern Observation for Efficient Long Reasoning