Petaflop-class on your desk
Run inference, RAG, agent workflows, and fine-tuning locally that previously needed cloud GPU rentals or a noisy workstation tower.
NVIDIA DGX · Delivered in MalaysiaPetaflop-class AI,
Petaflop-class AI,
on your desk.
NVIDIA's GB10 Grace Blackwell Superchip in a compact desktop, with 128 GB of coherent memory and the full DGX OS software stack pre-installed. Four OEM variants. EMARQUE handles the local setup, network onboarding, and warranty handoff so you can focus on shipping AI.
●NVIDIA-Powered4 OEM VariantsFrom RM 15,888Local Warranty
GB10Grace Blackwell SuperchipNVIDIA's Arm-based AI chip with Blackwell GPU and 20-core CPU on one die.
128GB unified memoryCPU + GPU coherent. Models stay in memory, no PCIe bottleneck.
DGX OSPlus AI Enterprise stackPre-installed NVIDIA software — CUDA, NIM, AI Workbench, vLLM, PyTorch.
Why DGX Spark
A compact AI supercomputer, four ways to spec it.
All four variants share the same GB10 Grace Blackwell chip and 128 GB of unified memory. The differences are storage capacity, chassis design, and price — pick the one that fits your buying constraints.
Unified memory architecture
128 GB of coherent CPU + GPU memory means models up to ~200B parameters can be loaded without the manual sharding and offload dance.
DGX software stack pre-loaded
DGX OS (Ubuntu-based) ships with NVIDIA AI Enterprise — CUDA, cuDNN, NIM microservices, AI Workbench, NeMo, vLLM, RAPIDS images.
Four OEM choices
Gigabyte AI TOP ATOM, MSI EdgeXpert MS-C931, ASUS Ascent GX10, and the NVIDIA Founders Edition — same chip, different chassis, cooling, and storage trade-offs.
Quiet, low-power, desk-friendly
Fits on a desk. Runs off a standard wall outlet. Quiet enough for a meeting room. No air-conditioning upgrade required.
EMARQUE local handoff
Local invoicing in MYR. EMARQUE specialists do site setup, network onboarding, and stack validation. Manufacturer warranty fulfilled locally.
OEM variants
Four DGX Spark SKUs — same chip, different chassis.
EMARQUE supplies all four DGX Spark OEM variants direct from NVIDIA's authorised channel. Live stock and per-SKU pricing on emarque.co; lead time noted at quotation.
Best value
Gigabyte AI TOP ATOM
RM 15,888
Starting price · MYR
- Storage
- 1 TB / 2 TB NVMe
Part of Gigabyte's AI TOP line for local AI prosumers. Compact chassis, tuned for sustained workloads.
Shop on emarque.coDesign-led
ASUS Ascent GX10
RM 19,699
Starting price · MYR
- Storage
- 1 TB / 2 TB / 4 TB NVMe
ASUS's workstation-grade Ascent design. Premium materials, business-aesthetic chassis.
Shop on emarque.coEdge-focused
MSI EdgeXpert MS-C931
RM 21,998
Starting price · MYR
- Storage
- 2 TB / 4 TB NVMe
MSI's edge-AI variant. Industrial-grade build, tuned for edge deployment scenarios.
Shop on emarque.coReference design
NVIDIA Founders Edition
RM 23,999
Starting price · MYR
- Storage
- 4 TB NVMe
NVIDIA's own reference design. The benchmark every OEM is tuned against.
Shop on emarque.coEMARQUE includes with every DGX Spark
- Unboxing, asset-tag registration, and warranty activation
- On-site or remote network onboarding (IP plan, DNS, firewall rules)
- Stack validation — runs your first model and produces a benchmark report
- 1-hour onboarding session for your team on DGX OS + AI Workbench
- Local warranty fulfilment — RMA shipped from Klang Valley, not from overseas
Use cases
What people are running on DGX Spark.
AI Development
Local model development and prototyping
Iterate on prompts, RAG pipelines, fine-tunes, and agents in the same environment you'd deploy at scale — without paying per token while you experiment.
RAG / Inference
Private RAG for individuals and small teams
Index your documents, run conversational search over them, all locally. Sensitive data never leaves the device.
Edge AI
On-site inference at remote locations
Factory floors, retail back rooms, field offices — bring AI to data that can't leave the site, on a unit small enough to ship in a single box.
Education
Teaching and lab-bench AI
Hands-on AI courses, capstone projects, and per-student dev environments without the lab provisioning a multi-GPU server.
Is this for you?
Client guidance — DGX Spark.
How EMARQUE scopes this system: who it suits, when to pick it, when to pick something else, and what we add beyond the hardware.
Who it's for
Individual developers, researchers, and small teams who want a real NVIDIA AI stack on the desk — without a server-room footprint or a cloud bill.
Choose this when
- You want to prototype and develop against the same software stack the data-centre runs (DGX OS, AI Enterprise, NIM, NeMo).
- Your models fit comfortably in 128 GB unified memory — up to ~70B with quantization.
- Edge or branch-office deployment where shipping a rack isn't realistic.
Pick something else when
- You need to serve more than a handful of concurrent users at production latency.
- Your fine-tuning runs need 4+ GPUs or > 128 GB of GPU memory.
- Your workload is heavily I/O-bound on bulk storage rather than GPU memory.
Best-fit workloads
- On-prem AI development, prototyping, and evaluation
- Private inference and RAG for individual developers and small teams
- LLM fine-tuning and quantization that fits 128 GB unified memory
- Edge deployments where a full server is overkill
Model & memory fit
Comfortably runs 7B–13B at FP16 and 30B–70B with INT4 / INT8 quantization. The 128 GB unified pool means CPU + GPU share memory — no PCIe shuttling for embeddings or KV cache.
Deployment shape
Sits under a desk, draws ≈ 240 W, quieter than most workstations. Standard 10 GbE plus Wi-Fi. No special HVAC or rack needed.
Alongside the rest of the lineup
Smaller and quieter than DGX Station; runs the same DGX software stack at ~5× lower price. Where a Mac Studio or a single-GPU workstation taps out at quantized 30B, the Spark handles 70B comfortably.
Upgrade path
When concurrent-user load grows beyond a small team, step up to AI PRO 500 (multi-GPU pedestal) or to DGX Station if the workload demands trillion-parameter local AI.
What EMARQUE adds beyond the hardware
- Local NVIDIA-powered systems specialist — MYR pricing, no FX surprises.
- Pre-flight: validate your OEM variant (Gigabyte / MSI / ASUS / FE) for the workload before shipping.
- DGX OS + AI Enterprise activation and stack sanity-check on delivery.
- Local warranty handling — no overseas RMA pipeline.
Next step
Get a DGX Spark configuration and lead time from your Malaysian NVIDIA systems specialist.
Platform specs
Common across every OEM variant.
NVIDIA defines the DGX Spark platform — every OEM variant ships the same chip, memory, OS, and software stack. Storage capacity and chassis are the per-SKU differences.
- Superchip
- NVIDIA GB10 Grace Blackwell
- CPU
- 20-core Arm
- Memory
- 128 GB unified (CPU + GPU coherent)
- Storage
- 1 TB / 2 TB / 4 TB NVMe (varies by OEM SKU)
- OS
- NVIDIA DGX OS (Ubuntu-based) + NVIDIA AI Enterprise stack
- Software included
- CUDA · cuDNN · NIM microservices · AI Workbench · NeMo · vLLM · RAPIDS images · PyTorch
- Form factor
- Compact desktop
- Power
- Standard wall outlet — no dedicated circuit needed
FAQ
DGX Spark in Malaysia — common questions.
What is the price of NVIDIA DGX Spark in Malaysia?
DGX Spark starts at RM 15,888 for the Gigabyte AI TOP ATOM variant and runs up to RM 24,999 for the NVIDIA Founders Edition with 4 TB NVMe. Pricing is in MYR and includes EMARQUE's local setup + warranty handoff. See the four-variant comparison above for current pricing per SKU.Which DGX Spark variant should I buy?
All four variants share the same GB10 Grace Blackwell Superchip and 128 GB unified memory — the differences are storage capacity, chassis design, and price. Gigabyte AI TOP ATOM is the best entry point for AI developers; ASUS Ascent GX10 has the most polished business aesthetic; MSI EdgeXpert is tuned for industrial edge deployment; NVIDIA Founders Edition is the reference design. We'll match you to the right one at quotation.What models can DGX Spark run locally?
With 128 GB of unified memory, DGX Spark comfortably runs models up to ~200B parameters with quantization (e.g. Llama 3 70B at FP8, GPT-OSS 120B at INT4). For full-precision fine-tuning the practical ceiling is ~70B. For trillion-parameter inference and training, the DGX Station GB300 is the next step up.Can DGX Spark replace a cloud GPU subscription?
For steady-state inference and development workloads — yes. The payback against pay-per-token cloud APIs is typically 6–14 months depending on usage. For occasional burst training of frontier models you still want cloud or a multi-DGX Station setup. We'll help you model the breakeven at quotation.Is the DGX Spark warranty handled locally in Malaysia?
Yes. EMARQUE coordinates with the OEM (Gigabyte, MSI, ASUS, or NVIDIA) on your behalf for any warranty claim. Diagnostics are done locally; if a unit needs replacement we manage the swap with the manufacturer. You always have one local point of contact — no chasing overseas RMAs.Does the DGX Spark need special power or cooling?
No. Runs from a standard 13 A wall outlet. Fits on a normal desk. Acoustics are designed for office placement, not a server room. No dedicated air-conditioning required.Can I bulk-order DGX Spark units for a fleet rollout?
Yes. We handle volume orders (10+ units) with consolidated invoicing, staggered delivery, asset-tag pre-registration, and a fleet-deployment runbook. Ask at quotation for the fleet pricing tier.
Get your DGX Spark.
Tell us which variant you want — or which use case you're solving and we'll recommend one. EMARQUE handles the paperwork, delivery, setup, and warranty handoff.
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