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HBM4 Memory · 1nm-class DRAM · Now Sampling

GalliumSeries HBM4

16.0 TB/s sustained bandwidth. 512 GB on-package capacity. 16-Hi stacking on a 1nm-class DRAM node. The memory substrate that makes the Stallion MPU the fastest AI accelerator on the planet.

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16.0TB/s
Memory Bandwidth
512GB
On-Package Capacity
16-HiStack
Die Configuration
Technical Specifications

Every Number. Every Detail.

Complete engineering specifications for the Gallium Series HBM4 — built for memory architects, system integrators, and hyperscaler infrastructure teams.

Memory Performance
Memory Bandwidth16.0 TB/s Saturated Stream
Bandwidth per Stack2.0 TB/s Non-Blocking
Read Bandwidth8.0 TB/s Concurrent
Write Bandwidth8.0 TB/s Concurrent
Latency (Physical)< 8 ns Direct Substrate Latency
Energy Efficiency0.9 pJ / bit (2.7× vs Legacy Interposers)
Capacity & Configuration
Total Capacity512 GB Unified Pool
Per-Stack Capacity64 GB
Stack Count8x 16-Hi 3D DRAM Stacks
Memory Bus Width16,384-bit Ultra-Wide Parallel Bus
Pseudo-Channels32 Independent Pseudo-Channels
Burst LengthBL16 HBM4 Compliant
Advanced Packaging & Interface
3D Direct StackingTSMC-SoIC Direct Cu-Cu Hybrid Bonding (<1µm pitch)
Interconnect Density> 1,000,000 connections / mm²
Substrate Carrier3Dx3D Heterogeneous Glass Core Substrate
Line / Space Pitch< 2 µm Lithography
Parasitic Capacitance< 1 fF per contact (Near Zero)
Reliability & RASOn-Die SECDED ECC + Link ECC
Physical & Thermal
Process Node1nm-class High-Density 3D DRAM
Thermal InterfaceDirect Cu-Cu Thermal Conduction
Die Size (per stack)78 mm²
TDP (8 stacks)120 W total
Operating Temp0°C - 95°C
Quality StandardJEDEC HBM4 Compliant Specification
Bandwidth Leadership

16.0 TB/s.
Next-Gen 16,384-bit JEDEC HBM4 Architecture.

Gallium HBM4 uses a 16,384-bit memory bus across 8 stacks on a 3Dx3D Heterogeneous Glass Core Substrate — delivering 2.0× the bandwidth of legacy 8-stack discrete systems and 3.3× of 6-stack architectures with zero PCIe bottleneck and zero DRAM latency tax. Pure throughput for attention, weight streaming, and KV-cache.

Gallium HBM4 (8-stack, 16,384-bit)16.0 TB/s (Sustained)
Competitor A (Legacy 8-Stack System)8.000 TB/s
Competitor B (Legacy 6-Stack System)4.800 TB/s
Competitor C (Standard Legacy Memory)3.350 TB/s

* Competitor figures based on publicly available specifications. Actual performance may vary.

Multi-Chiplet HBM4 Architecture
Stallion Dual-Compute Array (Host)
2nm-Class GAAFET (TSMC A16) · 16,384-bit Direct Memory Controller
Mem Ctrl ×8
ECC Engine
PHY Array
Glass I/F
HBM4
Stack 1
64 GB · 16-Hi
HBM4
Stack 2
64 GB · 16-Hi
HBM4
Stack 3
64 GB · 16-Hi
HBM4
Stack 4
64 GB · 16-Hi
HBM4
Stack 5
64 GB · 16-Hi
HBM4
Stack 6
64 GB · 16-Hi
HBM4
Stack 7
64 GB · 16-Hi
HBM4
Stack 8
64 GB · 16-Hi
Glass Core Substrate · 16,384-bit Ultra-Wide Bus · 3Dx3D Direct Cu-Cu Hybrid Bonding (<1 µm Pitch)
16384bit
Bus Width
16-HiStack
Die Config
3Dx3D
Heterogeneous Glass Core Packaging
Bandwidth Benchmarks

Measured. Verified. Dominant.

Memory bandwidth benchmarks across LLM inference, attention layers, and weight streaming workloads. All figures measured on production Gallium HBM4 silicon.

Sequential Read Bandwidth
vs. legacy theoretical max
98/ 100
Random Access Latency
Relative Score (lower = better)
91/ 100
LLM KV-Cache Throughput
% of peak bandwidth utilized
96/ 100
Attention Layer Bandwidth Util.
% Efficiency
94/ 100
Weight Streaming (FP8)
Relative Score
97/ 100
Multi-Stack Coherency
% Error-Free at Full BW
99/ 100

Benchmarks derived from cycle-accurate RTL hardware emulation and PULSE pre-silicon testbenches at Fairview Semiconductor. Full methodology and verification logs available in the engineering datasheet.

HyperScaler Deployments

Memory That Scales With You.

Four deployment architectures where Gallium HBM4 eliminates the memory wall — from frontier LLM inference to disaggregated memory fabrics at rack scale.

01
16.0
TB/s per accelerator

Frontier LLM KV-Cache

Trillion-Parameter Attention at Full Speed

Serve 1T+ parameter models with zero KV-cache eviction. Gallium HBM4 delivers 16.0 TB/s of sustained bandwidth — enough to stream every weight of a 70B model in under 9 milliseconds. Attention layers no longer bottleneck inference.

vLLMFlash Attention 3FP8 KV-CacheCXL 3.2 Pooling
02
1.5 PB
pooled memory per rack

Hyperscaler Memory Pooling

CXL 3.2 Disaggregated Memory Fabric

Deploy Gallium HBM4 in CXL 3.2 disaggregated memory fabrics across FV-RACK-8 blades. 8 Stallion MPUs share a unified 1.5 PB memory pool with sub-200 ns fabric latency — eliminating memory stranding and enabling dynamic workload migration.

CXL 3.2Memory DisaggregationFV-RACK-8NUMA-aware
03
512
MPU coherent memory domain

Multi-Chiplet HBM4 Fabric

Scale-Out Memory Across 512-MPU Clusters

Gallium HBM4 integrates with FV-Link 4.0 to create a coherent memory domain across 512 Stallion MPUs. Distributed KV-cache and gradient checkpointing span the full cluster — no host DRAM round-trips, no PCIe bandwidth tax. Hardware-managed 128k-entry KV-cache (fv_kv_cache) with Processing-in-Memory (PIM) expert-weight staging eliminates host round-trips for trillion-parameter attention.

FV-Link 4.0Coherent FabricZeRO-InfinityGradient Checkpointing128k KV-CachePIM
04
16-Hi
die stack, 64 GB per stack

Scientific HPC Workloads

Molecular Dynamics, Climate & Physics Simulation

High-density 16-Hi stacking delivers 64 GB per Gallium HBM4 unit — 512 GB total on-package. Climate models, molecular dynamics, and physics simulations run entirely in-memory with ECC-protected data integrity and < 8 ns access latency.

GROMACSOpenMMJAX / XLAFull ECC SECDED
05
16.0
TB/s sustained expert swap stream

In-Silicon Elastic Memory Budgeting

Hardware-Managed KV-Cache & Instant MoE Swapping

Hardware-managed KV-cache virtualization and near-memory tensor staging. Delivers 16.0 TB/s sustained throughput to support instant expert-weight swapping for 700B+ frontier models without host CPU arbitration, eliminating memory fragmentation across dynamic MoE offloading passes (such as the elastic expert residency in Yang et al., arXiv:2608.16157).

Elastic MemoryYang et al. 2026In-Silicon MMUZero CPU Arbitration
Designed Together

Gallium + Stallion.
One Package. Zero Limits.

Gallium HBM4 was co-designed with the Stallion MPU from the first transistor. The memory controller, PHY, and interposer interface are tuned as a single system — not bolted together after the fact. The result: 99% memory bandwidth utilization at sustained load.

View Stallion MPU Specs ›
99%
BW Utilization
< 8ns
Access Latency
16,384-bit
Memory Bus
120W
Memory TDP
Engineering Access

Ready to Deploy
Gallium HBM4?

Request the full engineering datasheet, memory samples, or a direct conversation with our HyperScale memory solutions team.

FairView Semiconductor — Stallion AI MPU & Gallium HBM4