If you want to rent RTX 3090 Asia capacity, you are probably after the cheapest practical way to get 24 GB of VRAM near your users or your team. The RTX 3090 is two generations old, but its memory is the same size as an RTX 4090's, and for many jobs memory is what decides whether a model runs at all. This article helps you decide whether a 3090 is enough, shows how to search for one across Asian countries on Cloudj, and explains where its limits are.
For the broader regional picture, start with the GPU cloud Asia guide.
Is a 3090 enough? A quick checklist
Answer these before you search:
- Does the model fit in 24 GB? If yes, a 3090 will run it. If it needs 32 GB or more, no 24 GB card will help.
- Is speed critical? The 3090 is slower than newer cards. For an overnight batch, that may not matter. For a live chatbot under load, it might.
- Do you need newer precision formats? Some recent optimisations (such as FP8 paths in certain inference engines) target newer architectures. Ampere cards like the 3090 may not benefit.
- How long will it run? Long jobs magnify any speed difference into real hours.
If you answered "fits, not critical, no, short or batch", the 3090 is a sensible choice.
What still fits on 24 GB
As general guidance, with exact needs depending on resolution, context length and software:
| Workload | On an RTX 3090 |
|---|---|
| SD 1.5 and SDXL image generation, LoRAs, ControlNet | Runs well |
| 7B to 13B LLMs, 4-bit or 8-bit | Runs well, with room for context |
| LoRA fine-tuning of 7B models | Practical with 4-bit or 8-bit base weights |
| Whisper-style speech recognition | Runs well |
| 30B to 34B LLMs in 4-bit | Possible but tight, short context only |
| Large video generation models | Often too slow or too large |
If your projects are mostly image generation for an online shop, a Vietnamese-language chatbot built on a 7B model, or transcription, the 3090 covers them. The Stable Diffusion GPU for Vietnamese users article shows a full image-generation setup on a 24 GB card.
Searching across Asian countries
On Cloudj, location is a country filter over a live list of host machines. Open the RTX 3090 deploy page and enter several codes in the Country field:
VN, SG, HK, TW, JPA few notes on this list. VN is worth including, but machines in Vietnam are not guaranteed to be listed, and Cloudj has no data centre of its own there. Singapore and Hong Kong are the usual nearby alternatives for Southeast Asia; Taiwan and Japan widen the choice further.
Each result shows the country (never a city), VRAM, vCPU, RAM, download speed, reliability, max duration, bandwidth price and a Datacenter badge where relevant. The list is sorted by total price, so the lowest-priced matching machine is at the top. If nothing is listed, stock changes during the day; check again later, lower the minimum reliability slightly, or try the alternatives below.
The cheapest GPU near Vietnam article goes deeper into widening a search for the lowest live price.
The RTX 3090 Ti and other 24 GB options
The RTX 3090 Ti is a slightly faster version of the same card, also with 24 GB. Search for it with the same codes; if it is listed at a similar price, it is a small free upgrade.
A smarter search is often by memory rather than name: clear the model, set a minimum VRAM of 24 GB and keep your country codes. You will see every 24 GB card listed, including 3090, 3090 Ti and 4090, and can pick the best total.
When the RTX 4090 is worth it
The RTX 4090 has the same 24 GB but a newer architecture and substantially more compute. It is worth the difference when:
- you serve many users at once and need more throughput from one card;
- your jobs run for many hours, so faster completion saves real money;
- your software benefits from Ada-generation features.
Since billing is per minute, a faster card can cost less per finished job even at a higher hourly price. Compare live "from" prices on the model pages and estimate total cost per job, not per hour. The RTX 4090 in Southeast Asia article covers searching for that card in the region.
Running a 3090 instance
Access is by SSH key only. The Connection tab shows the host and port:
ssh -p <port> root@<host>
nvidia-smiUse the Ubuntu + CUDA or PyTorch + JupyterLab template and install your tools over SSH. Choose disk size generously; it cannot be changed later. Each machine is an independent host with an "available until" date, so keep your models and outputs backed up. When you finish, destroy the instance; stopping keeps charging for storage and releases the GPU.
FAQ
Is the RTX 3090 always available in Asia?
No. Stock changes during the day. Search with your codes; if a machine is listed, you can deploy it.
Can a new account rent an RTX 3090?
Yes, it is a consumer GPU, which new accounts can rent. Datacenter cards need a higher account level.
Will SDXL run on a 3090?
Yes, comfortably at common resolutions, including LoRAs and ControlNet.
Should I try VN first?
You can include VN in the filter, but Vietnamese machines are not guaranteed. Always add SG and HK as well.
Find a 24 GB card nearby
Open the RTX 3090 deploy page, enter VN, SG, HK, TW, JP and see what is listed now. Compare live prices for every 24 GB card on GPU cloud.