GPU Architecture
GB10 Blackwell
5th-gen Tensor Cores with SM 10.0. Native NVFP4 quantization for 3× faster inference without accuracy loss. The architecture cloud providers charge 6–10× more for — when they have it at all.
NVIDIA GB10 Blackwell · Available Now · No Waitlist
The Hardware Everyone Wants.
Available Now.
Dedicated NVIDIA DGX Spark — 128GB unified memory, Blackwell architecture — for developers, researchers, and builders who are done waiting. No broker markups. No enterprise contracts. No hidden fees. Flat $0.55/hr.
128 GB
Unified Memory
1 PFLOP
FP8 Performance
200B+
Param Models
$0.55
Flat Hourly Rate
// Why This Exists
The Frontier Is Moving.
The Frontier Is Moving.
Not Everyone Gets In.
There’s a new divide in AI development.
On one side: well-funded labs, enterprise teams, and the rare individual lucky enough to lock in a contract before inventory disappeared. On the other: developers, researchers, students, and founders who know exactly what they want to build — and can’t get to the hardware to do it.
GPU availability is broken. Broker bots snap up instances the moment they appear and flip them at 2–3× markup. Build your own rig? You’re $15,000+ in before you’ve written a line of code — on hardware that may not run next month’s model. Enterprise cloud providers that do carry Blackwell want a 12-month commitment and thousands per month before you’ve validated a single workflow. And the cheap shared options? You’re one host reboot away from losing a 12-hour training run and every hour of work that went into it.
The people getting ahead right now aren’t necessarily smarter. They just have access.
SparkyHosting exists to change that.
from openai import OpenAI
# Drop-in compatible — change base_url and api_key only
client = OpenAI(
base_url="https://api.sparkyhosting.com/v1",
api_key="spark_your_session_token",
)
response = client.chat.completions.create(
model="dgx-spark-gb10",
messages=[{
"role": "user",
"content": "Explain CUDA memory coalescing",
}],
stream=True,
)
for chunk in response:
print(chunk.choices[0].delta.content, end="")Two lines of code. That’s the migration.
Change base_url and api_key. Everything else you’ve already written works immediately.
// Hardware
Built on Blackwell.
Built on Blackwell.
Finally Accessible.
The NVIDIA GB10 superchip delivers data-center-class AI performance. Until now, getting access to it meant enterprise contracts, broker markups, or a $15,000 build. Not anymore.
Unified Memory
128 GB
273 GB/s bandwidth. Load a 120B model, a 6.7B coder, and a 4B embedding model simultaneously — all in memory. Run what you actually want to run, not what fits.
NVMe Storage
1 TB
Ephemeral or persistent NVMe. Ultra-fast dataset loading and checkpoint saves. Your work survives your session — no more losing 12-hour training runs to infrastructure problems.
AI Performance
1 PFLOP FP8
2nd-gen Transformer Engine, 2× attention speedup. This is a development and training environment — purpose-built for loading large models, training on private data, and benchmarking before you commit to production. Not the right tool for high-throughput production inference. The right tool for everything before that.
Access Mode
SSH + Docker
Full root access. CUDA 12.8, cuDNN, PyTorch, and NVIDIA AI Enterprise stack pre-installed. No 40-minute spin-up wait. No framework setup. You’re in and working in seconds.
Instance Type
100% Dedicated
No shared tenancy. No noisy neighbors. No spot evictions. When you’re running, you’re the only one running. Your session, your hardware, your data — no one else’s job can interrupt yours.
// Comparison
6× Cheaper Than H100.
6× Cheaper Than H100.
And Actually Available.
Price is only part of the story. The H100, H200, and B200 you see listed on other platforms are often waitlisted, spot-only, or available through broker services at 2–3× markup. The DGX Spark is available today — dedicated, bare-metal, no contract. What you see is what you pay.
| GPU | Architecture | VRAM | Hourly | Monthly | Availability |
|---|---|---|---|---|---|
| NVIDIA DGX Spark — SparkyHosting Best Value | Blackwell GB10 | 128 GB | $0.55 | $350 | ● Now |
| NVIDIA H100 | Hopper SXM5 | 80 GB | $2.95 | ~$2,154 | Waitlisted |
| NVIDIA H200 | Hopper SXM5 | 141 GB | $3.50 | ~$2,555 | Waitlisted |
| NVIDIA B200 | Blackwell SXM6 | 192 GB | $5.50 | ~$4,015 | Contract Required |
// Why Builders Trust SparkyHosting
Pricing
Flat Rate. Always.
$0.55/hr. No egress fees. No bandwidth surcharges. No billing surprises. What you see in pricing is exactly what hits your card.
Hardware
Dedicated. Every Session.
No shared tenancy, no spot evictions, no noisy neighbors. When you’re running, the DGX Spark is yours — completely.
Privacy
Your Data Stays Yours.
Every environment is isolated to a single user. Nothing you load, run, or train is accessible to anyone else — and it is never used to train external models.
Support
Real Support. Real People.
Not a ticket queue. Not a forum thread. We’re builders who came from data center operations. When something needs attention, a person responds.
// Use Cases
Stop Waiting. Start Building.
If you’ve hit the wall — VRAM limits, unavailable inventory, enterprise friction, or the creeping feeling that the frontier is moving without you — this is what the other side of that wall looks like.
Independent AI Builders
You know what you want to build. The hardware has been the bottleneck. 128GB of dedicated Blackwell memory means the model you’ve been reading about is the model you actually get to run — not a quantized approximation that fits in 24GB.
ML Research
Develop novel architectures on the same Blackwell silicon used in production data centers — without waitlists, without broker markups, and without signing away 12 months of budget to access it.
Private AI Workflows
Why are you sending proprietary data to a model that may train on it? Every prompt to a frontier API is potentially your financial records, client data, or competitive research becoming someone else’s training set. A dedicated SparkyHosting environment keeps your data isolated, private, and entirely under your control.
Multi-Agent Systems
Running a multi-agent stack on constrained hardware means constant swapping, degraded context, and throughput that makes demos look better than they are. 128GB unified memory puts your planner, executor, and specialist models in memory simultaneously — zero swapping, real performance.
AI Education
Stop teaching the next generation of AI engineers on rate-limited APIs and shared cloud slices. Real hardware means real learning. The gap between a shared API and dedicated Blackwell silicon is the gap between a parking lot and a highway.
Production Benchmarking
Before you commit to $100,000 in production infrastructure, validate your throughput, latency, and cost on real Blackwell silicon. Rent what you need for a sprint. Make the decision with data — not vendor promises.
// Why We Built This
We Built This Because
We Built This Because
We Couldn’t Find It Either
Renevar is a cybersecurity and AI infrastructure firm. We spent months trying to find a reliable way to run large language models privately — not to send client data to public APIs, not to pay enterprise cloud rates, not to sit on a waitlist or get outbid by broker bots.
We needed a private AI environment. One we could point at sensitive data, configure completely, and trust fully.
We bought a DGX Spark, tested it, and realized: if we needed this and couldn’t find it, others did too.
That’s SparkyHosting. Built for developers, researchers, and teams who need real dedicated AI infrastructure — not a shared API, not a spot instance that vanishes mid-run, and not a 12-month enterprise commitment before you’ve proven the concept.
// Pricing
Most Popular
Simple. Transparent. No Surprises.
Flat rate. No egress fees. No storage surcharges. No contracts. No broker markup. The price you see is the price you pay — billed to the minute, cancelled whenever you want.
Pay As You Go
$0.55/hr
Billed per minute · No minimum · No commitment
- SSH + Docker access
- CUDA 12.8 & full NVIDIA AI stack pre-installed
- 1 TB NVMe storage (ephemeral)
- 100% dedicated environment — no sharing, no evictions
- No egress fees, no hidden charges
- Founder support during beta
- Cancel anytime
Unlimited Monthly
$350/mo
~$0.48/hr · 24/7 dedicated Blackwell environment · No surprises
- 24/7 dedicated DGX Spark environment
- Full root access
- Persistent 1 TB NVMe storage — your data survives your session
- SSH + Docker
- Priority founder support
- Guaranteed availability — your slot is yours
- Lock in beta pricing before it changes
Education & Team
Custom
Volume pricing for institutions, research programs, and AI teams
- Multi-seat access
- Isolated per-student environments
- Usage reporting dashboard
- Priority queue for class labs
- Dedicated onboarding support
- Invoice billing available
All plans include Ubuntu 22.04, CUDA 12.8, cuDNN, PyTorch & NVIDIA AI Enterprise stack.
Flat rate. No egress fees. No storage surcharges. No billing surprises. Ever.
// FAQ
Honest Answers.
Three things: dedicated hardware, flat pricing, and availability.
Dedicated: Unlike marketplace platforms that run your workloads on community-hosted machines, every SparkyHosting environment is dedicated bare-metal. No shared tenancy, no noisy neighbors, no spot evictions. Your job doesn’t get interrupted because someone else signed a contract.
Flat pricing: $0.55/hr. No egress fees, no bandwidth surcharges, no billing surprises. What you see is what you pay.
Available: The DGX Spark is here, now, without a waitlist. No refreshing availability pages. No broker markups.
Dedicated: Unlike marketplace platforms that run your workloads on community-hosted machines, every SparkyHosting environment is dedicated bare-metal. No shared tenancy, no noisy neighbors, no spot evictions. Your job doesn’t get interrupted because someone else signed a contract.
Flat pricing: $0.55/hr. No egress fees, no bandwidth surcharges, no billing surprises. What you see is what you pay.
Available: The DGX Spark is here, now, without a waitlist. No refreshing availability pages. No broker markups.
Yes. SparkyHosting runs on dedicated bare-metal hardware, not spot instances or community-hosted machines. Your environment is yours for the duration of your session — no evictions, no mid-run interruptions because someone else signed a contract. On the Unlimited Monthly plan, your environment is reserved and available 24/7.
$0.55/hr on Pay As You Go. $350/mo on Unlimited Monthly. That is the entire cost. No egress fees, no bandwidth charges, no storage surcharges, no reliability tax. What you see in pricing is exactly what hits your card.
SSH credentials are provisioned immediately after signup. Docker is pre-configured, CUDA 12.8 is installed, and the full NVIDIA AI stack is ready. You’re working within seconds of logging in — not after 40 minutes of spin-up and framework setup.
Yes. With 128 GB unified memory you can run models up to 200B parameters. NVFP4 quantization combined with Speculative Decoding enables 3× faster inference with full models resident in memory — no paging, no swapping.
Yes. Change the
base_url and api_key in any OpenAI SDK client and your existing code works immediately. Compatible with LangChain, LlamaIndex, Cursor, AutoGen, and more. No refactoring. No migration overhead.Completely. Every environment is isolated to a single user — no shared resources, no multi-tenancy. Your models, datasets, and runs are fully isolated. Nothing you load, train, or generate is accessible to anyone else, and it is never used to train external models. On the Unlimited plan, persistent NVMe storage retains your data between sessions.
Yes — and it’s one of the most underserved use cases in AI education. Most students are learning on rate-limited APIs and shared clusters that can’t run the models that actually matter at the frontier. Education plans include isolated per-student environments, usage dashboards, priority queue access, and invoice billing. Students get real Blackwell hardware — not a shared API with guardrails. Contact us for institutional and volume pricing.
For raw inference throughput on production workloads, dedicated H100 or B200 clusters are faster. We’ll be direct about that. The DGX Spark is purpose-built for AI development, training, and experimentation — not high-throughput production inference. What it does better than anything at this price point: loading large models (up to 200B parameters), training on private data, running multi-agent stacks, and benchmarking before you commit to production hardware. If you need production inference at scale, we’ll tell you that honestly. If you need a serious development environment — available today, at a price that makes sense — this is it.
Ubuntu 22.04 LTS, CUDA 12.8, cuDNN, NVIDIA Driver 535+, Docker, Python 3.11, PyTorch, and the full NVIDIA AI Enterprise stack. Root access lets you install anything else without restrictions. You don’t need to configure a CUDA environment from scratch — it’s ready when you log in.
The Frontier Isn’t Closed.
You Just Need the Right Hardware.
Stop refreshing availability pages. Stop negotiating with enterprise sales teams for access to hardware you need this week. Stop paying broker markups for spot instances that can vanish mid-run.
Your dedicated DGX Spark environment is here. Flat $0.55/hr. No waitlist. No contracts. No surprises.
The people getting ahead right now aren’t smarter — they just have access. Now you do too.