Available
Best value
RTX 4090
24GB VRAM for ComfyUI, Flux, Stable Diffusion, LoRA tests and batch image jobs.
- From
- $0.39/h
- Daily
- from $8.90
- Monthly
- from $249
China-based GPU capacity for AI workloads
Select GPU, see price, start setup
Transparent GPU resources for cost-sensitive AI training, fine-tuning, ComfyUI, image/video generation and batch inference. Pick a resource, submit your contact, then we confirm stock and prepare access.
- Setup after confirmation
- 30 min
- RTX 4090 from
- $0.39/h
- Validation test
- 2 hours
Resource menu
Choose the GPU before you contact us
Prices are starting points for China/Asia-based resources. Final availability, region, bandwidth and rental length are confirmed before payment, so customers see a budget first and only confirm details afterward.
Limited
New demand
RTX 5090
32GB VRAM for newer image/video workflows and local model experiments.
- From
- $0.79/h
- Daily
- from $18
- Monthly
- from $549
Available
80GB VRAM
A100 / A800
80GB class resources for LLM fine-tuning, larger inference tests and memory-heavy jobs.
- From
- $1.19/h
- Daily
- from $28
- Monthly
- from $799
Limited
Inference
L40S / A40
48GB class resources for inference services, rendering, CV workloads and mid-size models.
- From
- $0.59/h
- Daily
- from $14
- Monthly
- from $399
Check stock
High-end
H100 / H200
High-end resources for serious training and large inference tests when stock is available.
- From
- $2.49/h
- Daily
- from $59
- Monthly
- custom
Manual
Same machine
Multi-GPU server
4x or 8x GPU on one machine for parallel jobs, team containers or fixed training windows.
- 4090 8x
- from $2.99/h
- A100 8x
- check stock
- Setup
- Docker / SSH
Bandwidth, storage, public IP, region and managed setup can affect the final price. Ask for a 2-hour paid validation test before daily, weekly or monthly rental.
China resource fit
Good for offline AI workloads. Not for every use case.
Good fit
- ComfyUI, Flux, Stable Diffusion and batch image generation.
- LLM fine-tuning, evaluation and offline training jobs.
- Batch inference where US/EU low latency is not required.
- AI agencies that need temporary capacity and human support.
Not ideal
- Ultra-low-latency US/EU production APIs.
- Strict data residency, compliance or enterprise procurement flows.
- Teams that require fully automated cloud deployment today.
- Workloads that cannot test network performance before rental.
Validation offer
Start with a paid 2-hour test
Use the test to verify GPU model, CUDA, PyTorch, Docker/Jupyter, network and your real workload. If it works, extend to daily, weekly or monthly rental with the same setup path.
01 Select GPU
02 Add Telegram or WhatsApp
03 Confirm stock and pay
04 Access prepared within 30 minutes
Trust package
Proof before you rent longer
Hardware proof
nvidia-smi, GPU model, VRAM, CPU, RAM, disk and driver version screenshots.
Runtime proof
CUDA, PyTorch, Docker and Jupyter validation with your requested environment.
Network proof
Bandwidth and latency samples for your region before a longer rental window.
Delivery proof
SSH, Jupyter or API endpoint handoff with a clear setup and extension path.
Popular searches
Focused pages for common GPU rental needs
Process
From selected resource to running workload
- 01Choose a GPU resource and submit email plus Telegram or WhatsApp.
- 02We confirm stock, bandwidth, region and whether China/Asia resource fits your workload.
- 03You book a paid 2-hour validation test or a longer rental window.
- 04After confirmation, we prepare SSH, Docker, Jupyter or runtime access within 30 minutes.
- 05Your team validates and extends to daily, weekly or monthly rental.
FAQ
Questions overseas teams ask first
Where are the GPU resources located?
Many resources are China/Asia-based. We state that upfront because it affects latency, compliance and network fit. For training, fine-tuning and batch work, this can still be cost-effective.
Is pricing final?
Listed prices are starting points. Final price depends on current stock, GPU count, rental length, bandwidth, storage, public IP and managed setup requirements.
Can you open access within 30 minutes?
After stock and payment are confirmed, we aim to prepare access within 30 minutes for standard resources. Complex Docker/Jupyter environments or multi-GPU machines may need extra setup time.
Can each GPU run as a separate container?
Yes for Docker-level GPU binding. RTX 4090 does not support NVIDIA MIG, so we describe this as container-level isolation rather than hardware MIG isolation.
Reserve resource
Select GPU and add a direct contact
Submit the resource you want, then add us on Telegram for the fastest stock confirmation. For urgent requests, include your workload, rental length and whether China/Asia latency is acceptable.