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HBM Downgrade Drives KV Cache Offload Demand
Last Modified
2026-09-21
Update Frequency
Aperiodically
Format
AI chip makers weigh downgrading HBM capacity, hitting capacity for KV cache, lifting offload memory demand, as 8hi stays mainstream.
Key Highlights
- Impact: Cuts hit inference, exposing capacity for KV cache as weights stay resident.
- Options: Each option comes with a tradeoff.
- Demand: Offloading lifts demand for higher bandwidth, low-latency memory.
- Outlook: NVIDIA, Google favor 8hi HBM; 4hi stays niche.
Table of Contents
- Introduction
- Impact of Capacity Downgrades Centers on Inference: HBM Primarily Accommodates Weights and KV Cache
- HBM Capacity Reduction Primarily Impacts KV Cache Availability; Costs Vary by Adjustment Method
- Consequences of Downgrading HBM Capacity
- Memory Hierarchy for KV Cache Offloading in AI Servers
- Mainstream AI Chip Suppliers Still Plan to Adopt 8hi and 12hi HBM Due to Supply-Side Practicality
<Total Pages: 6>
Sector: AI Server / Data Center Memory & Storage
Tag: HBM CoWoS Liquid Cooling Enterprise SSD ASIC AI Chip AI Accelerator Server Memory GDDR QLC NAND TSV AI Storage AI Inference AI Server AI Training Server HBM3 HBM4 Server GPU AI Capex ASP Competitive Landscape CSP Market Bulletin Market Share Market Size Penetration Rate Pricing Power Pricing Trends Production Capacity Revenue Shipments Supply Chain Supply & Demand Industry Datasheet
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