GPU Compute
$0.15
per GPU hour · RTX 3090
- RTX 3090 · 24 GB GDDR6X
- 10,496 CUDA cores
- PyTorch, TF & CUDA images
- Persistent volumes
- Hourly billing, no lock-in
- SSH & API access
15× cheaper than AWS GPU on-demand · See comparison
GPU Compute
GPU Compute
for AI Engineers.
High-performance RTX 3090 compute and S3-compatible storage. Transparent hourly pricing, a clean API, zero enterprise overhead.
- $0.15per GPU hour
- $2.49per TB / month
- <60sdeployment time
- API-firstdeveloper access
GPU Hosting
RTX 3090 compute, ready in seconds.
24 GB GDDR6X memory, 10,496 CUDA cores, and tensor performance tuned for modern AI workloads, provisioned through a clean API, priced by the hour.
- Hourly billing. Pay only for what you run
- Pre-baked images for PyTorch, TensorFlow & CUDA
- Persistent volumes and snapshot support
- Direct SSH and API-based orchestration
- Spin up in under 60 seconds
gpu-node-01 · running
LIVE
GPU Model
RTX 3090 · 24 GB GDDR6X
Utilization
VRAM Used
CUDA Cores
10,496
API key required. Set
BHK_API_KEY before launch
# export BHK_API_KEY=bhk_sk_live_4a2e8b1c9d7f3a5b
$ bhk gpu launch --type rtx3090
→ instance gpu-node-01 ready in 42sAPI Storage
Scalable storage with first-class API access.
S3-compatible object storage tuned for model assets, application data, and high-throughput pipelines. Predictable per-TB pricing, zero egress fees.
- S3-compatible API, a drop-in for existing tooling
- Tiered pricing for hot, warm, and archival data
- Strong consistency and regional durability
- Signed URLs, lifecycle rules, and versioning
- Zero egress fees between GPU and storage
bucket: ml-checkpoints
Throughput
Objects
2.4 M files · 847 GB used
Durability
99.999999999% · 3-zone erasure
Requires BHK access key and secret. See dashboard
$ aws s3 cp ./model.bin s3://ml-checkpoints/ \
--endpoint-url https://s3.bhkcloud.com
upload: 14.2 GB in 9.1sHow It Works
Deploy in three steps.
From first contact to running GPU workloads in under two minutes.
01
Contact & Get Access
Reach out via our contact form or schedule a demo. We'll configure the right plan for your workload and provision your account.
02
Launch via API or CLI
Spin up GPU nodes and storage buckets with our clean REST API or CLI. Pre-baked images get you from zero to training in seconds.
03
Scale & Pay as You Go
Pay only for compute and storage you actually use, billed by the hour. No minimums, no commitments. Scale down anytime.
Pricing
Transparent, usage-based pricing.
No hidden fees. No annual commits. No enterprise lock-in.
API Storage
$2.49
per TB / month · zero egress
- S3-compatible API access
- Hot, warm & archival tiers
- Versioning & lifecycle rules
- Signed URLs & CDN support
- Strong consistency
- 11-nines durability
Enterprise
Custom
dedicated capacity & SLAs
- Dedicated GPU nodes
- Reserved capacity
- Custom SLA & uptime
- Priority support
- Multi-region options
- Volume discounts
Interactive Estimator
GPU Compute
100 hrs
Object Storage
5 TB
Est. monthly cost
$22.45
All plans include API access and usage-based billing. Need committed capacity? Talk to us →
Why BHK Cloud
Simple pricing. No bloat.
We cut the enterprise overhead so you get better pricing and a faster developer experience.
| Feature | BHK Cloud | Hyperscaler |
|---|---|---|
| RTX 3090 GPU / hour | $0.15 | $0.90+ |
| Object storage / TB | $2.49 | $23+ |
| Minimum commitment | None | Often required |
| GPU deployment time | < 60 seconds | 2 – 10 minutes |
| API complexity | Clean, simple REST | Dozens of services |
| S3 compatibility | Drop-in compatible | Native |
Hyperscaler rates based on public on-demand pricing as of 2026. Actual savings vary by usage pattern.
Platform
Built for performance. Priced for builders.
A focused infrastructure stack without the enterprise bloat.
01
RTX 3090 compute power
24 GB VRAM and 10,496 CUDA cores ready for training, inference, and rendering pipelines.
02
API-ready infrastructure
Spin up nodes, attach volumes, and stream data through clean, well-documented endpoints.
03
Scalable object storage
Grow from gigabytes to petabytes without re-architecting. Pay only for what you use.
04
Hourly GPU pricing
Starting at $0.15/hr, built so experimentation never gets billed like enterprise production.
05
Developer-first deployment
CLI, REST API, and infra-as-code patterns. No clicking through 40 settings panels.
06
Secure & reliable
Encrypted data at rest and in transit, regional durability, and strong consistency guarantees.
FAQ
Common questions.
Everything you need to know before getting started.
How does hourly GPU billing work?
You're billed for every hour (or fraction thereof) your GPU node is running. There are no minimum commitments. Spin up for a single experiment and shut down when done. Billing stops the moment you terminate the instance.
Is the storage S3-compatible?
Yes. BHK Cloud storage is fully S3-compatible, so you can point your existing AWS CLI, boto3, or any S3 SDK at our endpoint without changing your code. Just set --endpoint-url https://s3.bhkcloud.com.
How fast can I deploy a GPU node?
Typical deployment time is under 60 seconds. Pre-baked images for PyTorch, TensorFlow, and CUDA are ready to go, so you can be running training or inference jobs within two minutes of launch.
Do you offer committed capacity or enterprise plans?
Yes. If you need reserved GPU nodes, dedicated hardware, custom SLAs, or volume-based pricing, contact our team. We'll put together a custom proposal based on your workload and timeline.
What workloads run well on RTX 3090?
The RTX 3090's 24 GB VRAM makes it excellent for LLM inference (up to ~30B parameter models), image generation (Stable Diffusion, ComfyUI), model fine-tuning, batch rendering, and video encoding. It's well-suited for anything that fits within 24 GB of VRAM.
How do I get started?
Fill in the contact form or schedule a demo call. We'll set up your account, walk you through the API, and have you running within the same business day.
Ready to deploy?
Tell us about your workload and we'll get you running on the right setup in minutes.