- What is HBM and why is it critical for AI chips?
- HBM (High Bandwidth Memory) is a 3D-stacked DRAM technology that delivers 5–10× the memory bandwidth of standard GDDR. AI training and inference workloads are memory-bandwidth-bound, making HBM essential for GPUs like NVIDIA H100/B200 and AMD MI300X. Each HBM stack uses through-silicon vias (TSVs) to vertically connect multiple DRAM dies.
- What is the difference between HBM3, HBM3E, and HBM4?
- HBM3 offers up to 819 GB/s per stack (used in H100/MI300X). HBM3E increases bandwidth to 1.18 TB/s per stack with higher density (used in H200/B200). HBM4, expected in 2025–2026, will use a new base-logic die architecture for 1.5+ TB/s per stack with up to 48GB capacity, targeting next-gen AI accelerators.
- Who are the major HBM suppliers and what is their market share?
- SK Hynix leads with approximately 50–55% market share, followed by Samsung at 35–40% and Micron at 5–10%. SK Hynix was first to mass-produce HBM3E and has secured the majority of NVIDIA supply contracts. Samsung is ramping its 12-high HBM3E, while Micron supplies select designs.
- How much does HBM cost per GB?
- HBM3 costs approximately $8–10 per GB ($200 per 24GB stack). HBM3E costs approximately $8–10 per GB ($300 per 36GB stack). HBM pricing varies by contract terms, volume, and supplier. HBM commands a 5–6× premium over equivalent DDR5 capacity due to the complex 3D stacking and TSV manufacturing process.