/* 7) Override Elementor theme default link-blue on menu items */ .jet-mega-menu-list > .jet-mega-menu-item:not(.menu-ai) > .jet-mega-menu-item__inner > a.jet-mega-menu-item__link{ color:#1f2937!important; } .jet-mega-menu-list > .jet-mega-menu-item:not(.menu-ai) > .jet-mega-menu-item__inner > a.jet-mega-menu-item__link:hover{ color:#0066CC!important; } /* 8) Dropdown arrow indicator on items that have submenu */ .jet-mega-menu-list > .jet-mega-menu-item.has-submenu > .jet-mega-menu-item__inner > a::after{ content:" \25BE";font-size:9px;margin-left:6px;color:#9ca3af;display:inline-block;vertical-align:middle; }
SAVE up to 10% off for New Domain Name. PROMO CODE : bigjuly22
|AGENTIC AI
✦ Ask AI
Bigdomain white logo

NVIDIA GPU Hosting Malaysia — Run LLMs & AI Workloads on RTX PRO 6000 Blackwell, RTX 4000 Ada & RTX 6000 Quadro

Malaysia’s first openly-priced RTX PRO 6000 Blackwell (96GB) GPU compute. Dedicated cards, real vCPUs, RM billing — no USD surprises, no setup fees, no lock-in. Built for DeepSeek, Qwen, GLM, Llama and every LLM you want to run yourself.

Get Started on WhatsApp View Plans & Pricing
Tencent Official Agentic Cloud Partner MDEC 100 Go Digital — Top 20 TSP MD (Malaysia Digital) Status 24/7 Malaysian Support
96GBVRAM on one Blackwell card — serves 70B-class models
4,000TOPS FP4 AI compute (Blackwell)
RM1,811/mo entry GPU plan (RTX 4000 Ada x1)
0setup fee · 0 lock-in · RM billing
What is GPU hosting? GPU hosting (GPU server rental) gives you a dedicated server equipped with NVIDIA graphics processors to run AI, machine learning and rendering workloads. Unlike normal web hosting, a GPU server parallel-processes millions of calculations at once — which is exactly what LLMs like DeepSeek, Qwen and Llama need to generate answers, train models and serve AI APIs.
Our USP

Why Big Domain for GPU & AI Hosting

Seven reasons Malaysian teams pick us over foreign clouds and quote-only local providers.

1

First Openly-Priced RTX PRO 6000 Blackwell (96GB)

Not “contact us for a quote”. Real RM prices on the page, today.

Published RM pricing below
2

RTX 4000 Ada (20GB) — the Professional AI Card, Locally

Entry AI inference card at a price your budget can feel.

From RM1,811/mo
3

Pay in Ringgit — No USD Surprises

FPX, local cards, Maybank billing. No foreign-exchange shock on your invoice.

Billed & paid in MYR
4

Zero Setup Fee, Zero Lock-In

Simple monthly billing. Cancel when you want.

Others charge RM500–1,599 setup
5

Free Managed LLM Deployment

We install Ollama / vLLM / DeepSeek / Qwen and hand you an OpenAI-compatible API the same day.

Free managed deploy add-on
6

One Bill, One Vendor: GPU + Domain + SSL + Backup

Your AI server, domain, SSL and backups under a single MYR invoice.

Bundled services
7

Local Support — English, Bahasa Melayu & WhatsApp

Malaysian engineers on WhatsApp, not a ticket queue in another timezone.

wa.link/wn5vxt
The Hardware

Three Dedicated NVIDIA GPU Tiers

Whole-card GPU passthrough with dedicated vCPUs — predictable performance for production AI, no noisy neighbours.

New — Blackwell

RTX PRO 6000 Blackwell Server Edition

Best for large LLMs & multimodal
  • 96GB GDDR7 ECC VRAM
  • 24,064 CUDA cores · 5th-gen Tensor cores
  • Up to 4,000 TOPS FP4 AI compute
  • 1,597 GB/s memory bandwidth
  • 176GB RAM · 16 dedicated vCPUs · 1TB NVMe (x1)
  • 40 Gbps in / 16 Gbps out
Fits: Qwen2.5-72B, DeepSeek-R1-Distill-70B, GLM-4.5-Air, 70B-class FP4/FP8, multimodal
from
RM8,616 /mo
Best Value

RTX 4000 Ada Generation

Best for entry AI inference & dev
  • 20GB GDDR6 VRAM
  • 6,144 CUDA cores · AV1 encode/decode
  • 26.7 TFLOPS FP32
  • 360 GB/s memory bandwidth
  • 16–128GB RAM options · 4–32 vCPUs · 500GB NVMe (x1)
  • 40 Gbps in / 16 Gbps out
Fits: Qwen3-8B/14B, DeepSeek-R1-Distill-7B/14B, GLM-4-9B, RAG & embedding pipelines, video transcoding
from
RM1,811 /mo
Reliable Workhorse

RTX 6000 Quadro

Best for sustained compute & rendering
  • 24GB GDDR6 VRAM
  • 4,608 CUDA cores · dual encoders/decoders
  • 672 GB/s memory bandwidth
  • 32GB RAM · 8 dedicated vCPUs · 640GB NVMe (x1)
  • 16TB transfer included (x1 plan)
  • 40 Gbps in / 10 Gbps out
Fits: DeepSeek-R1-Distill-32B (Q4), Qwen3-32B (Q4), 3D rendering, long-running batch inference
from
RM5,175 /mo
For LLM & Machine Learning

Why a Dedicated GPU Beats Paying per Token

Every model below is open-weight — you own the weights, we provide the silicon. No per-token API bills, no rate limits; your data stays yours.

1

70B-class on ONE card

96GB Blackwell runs Qwen2.5-72B at FP8/INT4 on a single GPU.

2

3,000+ tokens/sec

Per card on 49B-class models (FP4, 100 concurrent) — real serving, not marketing.

3

~19x inference throughput

Blackwell generation vs previous-gen RTX 4000 Ada-class cards.

4

Up to 2.1x tokens per dollar

Compared with comparable GPU plans — the LLM-serving cost king.

5

Whole-card passthrough

Dedicated GPU + dedicated vCPUs. Predictable performance for production APIs.

6

Egress up to 90% cheaper

Outbound transfer costs far less than hyperscaler per-GB fees.

Plans & Pricing

GPU Hosting Prices in Malaysian Ringgit

Transparent Ringgit pricing. No setup fees, no lock-in — simple monthly billing.

PlanSpecsRM/mo
RTX PRO 6000 Blackwell x1176GB RAM · 16 vCPU · 1TB NVMeRM8,616
RTX PRO 6000 Blackwell x2352GB RAM · 32 vCPU · 2TB NVMeRM17,233
RTX PRO 6000 Blackwell x4704GB RAM · 64 vCPU · 4TB NVMeRM34,466
PlanSpecsRM/mo
RTX 4000 Ada x1 Small16GB RAM · 4 vCPU · 500GBRM1,811
RTX 4000 Ada x1 Medium32GB RAM · 8 vCPU · 500GBRM2,308
RTX 4000 Ada x1 Large64GB RAM · 16 vCPU · 500GBRM3,302
RTX 4000 Ada x1 X-Large128GB RAM · 32 vCPU · 500GBRM5,289
RTX 4000 Ada x2 Small32GB RAM · 2x GPU · 1TBRM3,622
RTX 4000 Ada x2 Medium64GB RAM · 2x GPU · 1TBRM4,616
RTX 4000 Ada x4 Small128GB RAM · 4x GPU · 2TBRM10,226
RTX 4000 Ada x4 Medium196GB RAM · 4x GPU · 2TBRM12,337
PlanSpecsRM/mo
RTX 6000 Quadro x132GB RAM · 8 vCPU · 640GB · 16TB transferRM5,175
RTX 6000 Quadro x264GB RAM · 2x GPU · 1.28TB · 20TB transferRM10,350
RTX 6000 Quadro x396GB RAM · 3x GPU · 1.92TB · 20TB transferRM15,525
RTX 6000 Quadro x4128GB RAM · 4x GPU · 2.56TB · 20TB transferRM20,700
Note: All prices in Malaysian Ringgit (MYR) and include management & infrastructure fees — no hidden charges, no setup fees. Simple monthly billing. Egress: Quadro plans include 16–20TB transfer; Blackwell & Ada plans bill outbound at a low per-GB rate — ask us about bundling a transfer allowance.
LLM Compute Guide

Which GPU Does Your LLM Need?

DeepSeek, Qwen, GLM, Kimi, Llama — a quick-fit guide for Malaysia’s AI builders.

Rule of thumb: FP16 ≈ 2x model params (GB), FP8 ≈ 1x, INT4/Q4 ≈ 0.5x — then add 15–30% for KV cache & runtime (more for reasoning models). MoE models (DeepSeek 1.6T, Qwen3.5-397B, GLM-5, Kimi K3) must load all weights into VRAM — active params only affect speed, not memory.

Tier 1RTX 4000 Ada — 20GB

Up to 14B models comfortably:

  • Qwen3.5-9B (Apache 2.0, multimodal)
  • DeepSeek-R1-Distill-7B / 14B
  • GLM-4-9B
  • RAG, embeddings, code completion, video transcoding

From RM1,811/mo — usually enough for most startups.

Tier 2RTX 6000 Quadro — 24GB

30B-class at Q4 — the reasoning sweet spot:

  • DeepSeek-R1-Distill-32B (Q4)
  • Qwen3.5-27B (Q4)
  • Qwen3.5-35B-A3B (Q4)
  • GLM-Z1-32B-A3B

Flagship reasoning quality on a single card — from RM5,175/mo.

Tier 3RTX PRO 6000 Blackwell — 96GB

Flagship-class on ONE card:

  • Qwen3.5-122B-A10B (Q4)
  • GLM-5-Air (Q4)
  • Qwen2.5-72B (FP8 / INT4)
  • DeepSeek-R1-Distill-Llama-70B (Q4/Q8)

From RM8,616/mo. Multi-GPU clusters (2–8x) for 284B–1.6T models.

Multi-GPUClusters — 2 to 8 cards

For the giants — talk to us, we’ll size it:

  • DeepSeek-V4-Flash (284B): 2x Blackwell · V4-Pro (1.6T): 8x+
  • Qwen3.5-397B-A17B: 3–5x Blackwell
  • GLM-5 (744B): 4x Blackwell
  • Kimi K3 (2.8T): API or 8x+ cluster

Free sizing consultation — WhatsApp us your model & workload.

Open-weight modelParamsVRAM at Q4Best Big Domain tierNotes
DeepSeek-R1-Distill-Qwen-7B7B~5GBRTX 4000 Ada (20GB)Full FP16 even; fast chat
DeepSeek-R1-Distill-Qwen-14B14B~10GBRTX 4000 Ada (20GB)Q4 comfortable
DeepSeek-R1-Distill-Qwen-32B32B~19GBRTX 6000 Quadro (24GB)Q4 sweet spot
DeepSeek-V4-Flash284B MoE (13B active)~120–150GB2x BlackwellMIT · 1M ctx · FP4+FP8 native
DeepSeek-V4-Pro1.6T MoE (49B active)~700–870GB8x Blackwell cluster / APIMIT · 1M ctx · frontier-class
DeepSeek-R1-0528 (full)671B MoE~400GB4–8x BlackwellReasoning; updated May 2026
Qwen3.5-9B9B~5GBRTX 4000 Ada (20GB)Apache 2.0 · multimodal
Qwen3.5-27B27B dense~16GBRTX 6000 Quadro (24GB)Q4
Qwen3.5-35B-A3B35B MoE~19GBRTX 6000 Quadro (24GB)Q4
Qwen3.5-122B-A10B122B MoE~65GBRTX PRO 6000 Blackwell (96GB)Flagship on ONE card (Q4)
Qwen3.5-397B-A17B397B MoE~210–400GB3–5x Blackwell / API256K ctx · Apache 2.0
Qwen2.5-72B72B~45GBRTX PRO 6000 Blackwell (96GB)FP8 / INT4 single card
GLM-4-9B9B~6GBRTX 4000 Ada (20GB)INT4
GLM-5-Air~67B active~85GBRTX PRO 6000 Blackwell (96GB)Q4 single card
GLM-5744B MoE (40B active)~380–456GB4x Blackwell / API200K ctx · MIT
Kimi K2.7~1T-class MoE~325GB (2-bit)4x Blackwell (Q2) / APIPractical local Kimi
Kimi K32.8T MoE (16/896 experts)~350–700GB (Q4)8x Blackwell (Q4) / API1M ctx · native MXFP4 ~1.4TB
Llama 3.1 / 3.3 8B8B~5GBRTX 4000 Ada (20GB)—
Llama 3.3 70B70B~41GBRTX PRO 6000 Blackwell (96GB)Q4/Q8
How It Works

Get Your GPU Server in 5 Steps

From enquiry to a working OpenAI-compatible API — same day.

1

Tell Us Your Model

WhatsApp us or send the enquiry — your workload, your model, your budget.

2

We Size Your GPU

Free consultation picks the right card — or cluster — for your LLM.

3

We Deploy & Optimise

Free managed setup: Ollama / vLLM / DeepSeek / Qwen, OpenAI-compatible API, same day.

4

You Connect & Scale

SSH/API access. Upgrade from 1 to 8 cards without re-provisioning from scratch.

5

One RM Bill

Domain, SSL, backups and GPU on a single Malaysian invoice. Cancel anytime.

FAQ

GPU Hosting Malaysia — Common Questions

What is GPU hosting Malaysia?
GPU hosting is renting a dedicated server with NVIDIA graphics processors for AI, machine learning and rendering workloads. It’s how you run open-weight LLMs (DeepSeek, Qwen, GLM, Llama) on infrastructure you control — without per-token API fees.
Can I run DeepSeek on your GPU servers?
Yes. DeepSeek-R1-Distill (7B–70B) runs on our single-GPU plans, and DeepSeek-V4-Flash (284B) runs on a 2x Blackwell server. The full V4-Pro (1.6T) needs a cluster — we’ll size it for you.
Do I need to be an AI engineer to use this?
No. We offer free managed deployment — we install and configure the model server and hand you a working OpenAI-compatible API.
What are the prices in RM?
GPU plans start at RM1,811/mo (RTX 4000 Ada x1) and RM8,616/mo (RTX PRO 6000 Blackwell x1). All prices are in Ringgit and include management fees. No setup fees.
Is there a setup fee or minimum contract?
No setup fee, no lock-in. Simple monthly billing — cancel when you want.
How do I pay?
In Ringgit — FPX, local cards and Maybank billing. No USD credit card needed.
Which GPU should I pick for a 7B or 14B model?
RTX 4000 Ada (20GB) is enough for most 7B–14B models at Q4 — even FP16 for 7B. For 30B+ models, step up to RTX 6000 Quadro (24GB), or RTX PRO 6000 Blackwell (96GB) for 70B-class.
Do GPU plans include data transfer?
RTX 6000 Quadro plans include 16–20TB transfer. Blackwell and Ada plans bill outbound at a low per-GB rate — ask us about bundling a transfer allowance.
Can I scale from 1 GPU to more later?
Yes — plans scale from 1 to 8+ GPUs. Upgrades are provisioned without re-architecting your stack.

Your LLM Deserves Its Own GPU.

Get a free sizing consultation — we’ll tell you exactly which card (or cluster) your model needs.

Get Started on WhatsApp Talk to Sales