All Flash
Shared NVMe Storage
Keep models, datasets, and checkpoints in one high-speed shared data layer—no copies, no silos.
E1001 Desktop AI Cluster
- Regular price
- $24,500.00
- Sale price
- $24,500.00
- Regular price
-
99 In Stock
More AI. Less Infrastructure.
Bring four GB10 nodes, shared NVMe storage, and a 200GbE data fabric into one local system. Spend less time moving data and assembling infrastructure—and more time running AI.
ENGINEERED FOR LOCAL AI
0
AI Data Fabric
Four 50GbE links deliver 200GbE of aggregate bandwidth for fast access to shared models and datasets.
4
AI Compute
Four GB10-powered nodes deliver up to 4 PFLOPS of combined AI compute and 512GB of unified memory.
Local & Private
Test RAG, LoRA, and inference workflows locally. Validate privately. Scale to H100 or B300 infrastructure when ready.
BUILT FOR
AI Development
Media Production
Education
Enterprise Knowledge
Research
Bioinformatics
Prove it locally. Scale it in the cloud.
Validate your AI workloads before committing to cloud-scale spend. E1001 Desktop AI Cluster helps you move forward with proven workflows, right-sized resources, and less waste.
THE DATA BOTTLENECK
Your compute shouldn’t wait on data.
Models live on one system. Datasets live on another. Every new task starts with another copy. E1001 brings it all into one high-speed local data layer.
Outgrowing Local Storage
Models, datasets, indexes, and outputs quickly fill workstation storage.
Model Checkpoints
Training Data
Vector Indexes
Generated Outputs
Data Everywhere
External drives, cloud folders, and local copies create duplication and confusion.
External SSDs
Cloud Folders
Local Copies
Version Conflicts
Compute Waiting on I/O
Fast GPUs lose valuable time when storage and networking cannot keep pace.
Slow Transfers
Repeated Copies
Idle Compute
Workflow Delays
Data Outside Your Control
Sensitive business, research, and creative data should stay under your control.
Data Ownership
Local Storage
Controlled Access
Data Residency
Validate first. Scale later.
Start at $30K—before committing
to an 8-GPU production system.
$30K+
VIVIBIT Validation Setup
$200K+
8-GPU Production System*
*Indicative 8-GPU system pricing: H100 / H200 / B300 systems ≈ $210K–$530K. Vendor pricing varies by configuration.
Prove the workflow—fast.
Validate RAG, agents, and LoRA.
No server room. No major upfront purchase.
4 Workloads
RAG · Agents · LoRA · AIGC
No Buildout
No Server Room Required
Scale out your DGX Spark setup.
Go from one GB10 node to four—
up to 512GB and 4 PFLOPS aggregate.
512GB
4 Nodes · Up to 4 PFLOPS
128GB
1 Node · Up to 1 PFLOP
*Aggregate figures are theoretical across four nodes. Usable scaling varies by workload and software.
Built for the desktop.
5× faster transfers.
90% less noise. No server room.
5×
Network Transfers*
90%
Less Noise*
*Based on VIVIBIT internal testing versus the reference configuration. Results vary by workload and environment.
What It Runs
Built for the full edge AI lifecycle—fine-tuning to deployment, single-node to cluster—across diverse high-performance AI scenarios
LLM Fine-Tuning
Efficient fine-tuning for billion-scale LLMs.
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Distributed Training
Scale to 4 PFLOPS with multi-node clusters.
Creative Design
Power real-time rendering and AIGC workloads.
Data Processing
Accelerate workflows with E1001 storage and networking.
Edge Inference
Deploy low-latency AI in manufacturing, healthcare, and more.
At a Glance
Four DGX Sparks vs. One Purpose-Built AI Cluster
See what changes when four standalone systems are connected by shared storage and a high-speed data fabric.
Feature
Four Standalone DGX Sparks
E1001 + Four DGX Sparks
Architecture
✕ Four independent systems
✓
One purpose-built cluster architecture
Storage
✕ Storage managed per node
✓
Shared NVMe data layer
Networking
✕ Networking requires integration
✓
Built-in 200GbE aggregate data fabric
Data Workflow
✕ Models and datasets may need copying
✓
Shared access to models, datasets, and checkpoints
Best For
✕ Independent workloads
✓
Shared data and multi-node workflows
BUILT AROUND DGX SPARK
Run More on GB10.
Unify Your Data with E1001.
Why E1001
Run scientific AI, visual intelligence, engineering models, and local agents on the NVIDIA CUDA ecosystem—while E1001 keeps datasets, model weights, checkpoints, and outputs in one shared all-flash data layer.
Technical Specifications
| model | DGX-Spark Cluster（4-Unit） |
| CPU | 80-Core ARM Processor |
| Storage | 16TB M.2NVMe SSD Max |
| Memony | 512GB LPDDR5x |
| GPU | NVIDIA GB10 |
| AI Performance | 4 PFLOPS |
| High-Speed Transfer | 2×100GbE+4×50GbE Switching |
| LAN(RJ45) | 4×10GbE |
| USB4 | 16×USB type-C |
| Audio Input | HDMI Multi-channel Audio |