Hardware Specifications - NVIDIA Grace Hopper Superchip

AI-Powered Capabilities

The GH200 platform with 144GB VRAM enables Eymbr to deliver enterprise-grade AI capabilities in a single-node footprint while maintaining complete air-gapped security

Extended Context Windows

Leverage 144GB VRAM and 432GB total unified memory for unprecedented context retention during complex investigations - massive GPU memory in a compact form factor.

131K token context window
432GB unified memory architecture
Dynamic allocation based on workload
Seamless context switching

GPU-Accelerated Search

Instant semantic search across conversations, documents, and training materials.

BAAI/bge-large-en-v1.5 embeddings
pgvector integration for similarity
LRU cache with CUDA OOM handling
Sub-second query response times

VRAM Document Store

Keep your team's knowledge and training materials in GPU memory for instant access.

Full-text storage in HBM3
Document type-aware chunking
Automatic citation generation
Zero-latency retrieval

Dynamic Resource Management

Intelligent allocation of GPU resources between AI models and data storage.

PagedAttention optimization
Automatic VRAM distribution
Priority-based allocation
Real-time performance monitoring

Local AI Inference

Run the powerful Qwen3-32B model entirely on-device for complete data security.

OpenAI-compatible API
No external dependencies
Enterprise-grade performance
Full model control

Multi-Model Architecture

Concurrent operation of language and embedding models for comprehensive analysis.

Lazy singleton initialization
Shared memory optimization
Automatic failover handling
Unified token management

Detailed Specifications

Processing Architecture
CPU	NVIDIA Grace CPU - 72x Arm Neoverse V2 cores
GPU	NVIDIA H100 Tensor Core GPU
Architecture	ARM64 (aarch64)
Interconnect	NVLink-C2C @ 900 GB/s bidirectional
Memory Configuration
Total Memory	432GB unified memory
GPU Memory (VRAM)	144GB HBM3 - massive VRAM in a single node
Memory Bandwidth	900 GB/s GPU memory bandwidth
Cache Coherent	Yes - CPU and GPU share memory space
ECC Support	Full ECC protection
AI Performance
FP8 Performance	3,958 TFLOPS with sparsity
FP16 Performance	1,979 TFLOPS with sparsity
Tensor Cores	4th Generation with Transformer Engine
MIG Support	Multi-Instance GPU capability
Software Requirements
Operating System	Ubuntu 22.04+ (ARM64)
CUDA Version	12.0 or higher
Python	3.10+
Storage	100GB+ SSD recommended
Security Features
Confidential Computing	Hardware-based security
Secure Boot	UEFI secure boot support
Memory Encryption	Available with CC mode
Air-Gap Ready	No external dependencies

NVIDIA GH200 ARM64 Platform