HBM3-16GB
SK Hynix HBM3 16GB memory stack with 1.2TB/s bandwidth for next-generation AI accelerators
Product Overview
Description
The HBM3-16GB is a 16GB High Bandwidth Memory stack featuring SK Hynix's cutting-edge HBM3 technology. With 1.2TB/s bandwidth, it delivers exceptional memory performance for next-generation AI training and HPC applications.
This HBM3 stack uses advanced 12-layer DRAM die stacking to achieve 16GB capacity with improved power efficiency. The 6.4GT/s data rate per pin is 2x improvement over HBM2E, enabling unprecedented memory bandwidth.
With 1024-bit interface and optimized power delivery, the HBM3-16GB is ideal for training large language models, scientific computing, and advanced AI research requiring maximum memory bandwidth and capacity.
Product Series
HBM
Primary Application
AI training accelerators
Key Features
- 16GB capacity with 12-layer stacking
- 1.2TB/s memory bandwidth
- 6.4GT/s data rate per pin (2x HBM2E)
- 1024-bit wide interface
- 1.1V operation for improved efficiency
- Advanced TSV technology
- Optimized for AI training workloads
Specifications
| Memory Type | HBM3 |
|---|---|
| Capacity | 16GB |
| Stack Layers | 12-Hi |
| Interface Width | 1024-bit |
| Data Rate | 6.4GT/s per pin |
| Bandwidth | 1.2TB/s |
| Voltage | 1.1V |
| Operating Temperature | 0C to +105C (Tcase) |
Applications
AI training accelerators
Electronic system design
Large language model training
Electronic system design
Scientific computing
Electronic system design
High-performance computing
Electronic system design
Advanced graphics
Electronic system design
Data analytics
Electronic system design
FAE Expert Insights
"The HBM3-16GB is the state-of-the-art in memory technology. The 1.2TB/s bandwidth is a game-changer for AI training - I've seen training times reduced by 30-40% compared to HBM2E systems. The 6.4GT/s data rate requires careful signal integrity design, but the performance gains are worth it. For LLM training with billions of parameters, this memory is essential. The 16GB capacity with 12-layer stacking is impressive engineering. If you're designing next-gen AI accelerators, HBM3 is the only choice."
Next-gen HBM3 performance for demanding AI training
— AI Memory FAE, BeiLuo
Frequently Asked Questions
What are the design considerations for HBM3?
HBM3 design considerations include: 1) Signal integrity - 6.4GT/s requires careful PCB and interposer design, 2) Thermal management - higher power density needs advanced cooling, 3) Power delivery - robust PDN for stable 1.1V operation, 4) Testing - requires high-speed test equipment, 5) Packaging - 2.5D packaging with advanced interposer. Engage with packaging partners early.