from 24 GBChat
Private ChatGPT · Qwen3 32B
A chat in your browser for writing, code and documents. No subscriptions and no message limits.
from €0.30/h · RTX 3090, 24 GB
Run AI models · Qwen
Run Qwen on a rented GPU
Qwen 32B in 4-bit fits on a single 24 GB card, and the 7B and 14B versions need 12 GB. Alibaba’s models are strongly multilingual, which makes them a common choice for chatbots in several European languages. If you just want a chat with no setup, there is a ready-made Private ChatGPT app on Qwen3 32B.
- App
- PyTorch
- GPU
- RTX 3060, 12 GB
- Price
- from €0.12/h
To launch, your balance must cover one hour of the machine. You are billed by the minute for actual use.
from 5 GBof video memory
2–5 minutesuntil the server is up
By the minutebilled from your balance
SSH and Jupyterserver access
How much memory you need and which GPU to pick
Qwen 2.5 7B takes about 5 GB of video memory in 4-bit; the cheapest suitable card is RTX 3060. Prices update from available catalogue machines when you open the page.
| Version | FP16 | 4-bit | Suitable GPUGPU | Price per hourPer hour |
|---|---|---|---|---|
| Qwen 2.5 7B | 16 GB | 5 GB | RTX 3060 | €0.12 |
| Qwen 2.5 14B | 31 GB | 10 GB | RTX 3060 | €0.12 |
| Qwen 2.5 32B | 71 GB | 22 GB | 2× RTX 3060 | €0.24 |
| Qwen 2.5 72B | 159 GB | 48 GB | 4× RTX 4060 Ti | €0.64 |
Estimate: FP16 ≈ 2 GB per billion parameters, 4-bit ≈ 0.6 GB, plus 10% for context. Pick: the cheapest configuration with enough memory; for large models that means several identical cards. All GPUs and prices
How to run Qwen in 3 steps
- Sign up and top up. Create an account and top up from €10. To launch, your balance must cover at least one hour of the chosen machine; after that you pay by the minute.
- Choose a GPU. Memory for each version is in the table above, and the lightest one runs from 5 GB. The button on this page selects the cheapest option with the PyTorch template.
- Run the model. The server is ready in 2–5 minutes. Open Jupyter in your browser or connect over SSH and run the commands below.
Finished? Stop the server in the dashboard and billing stops. Save and stop keeps /workspace for €0.03 per GB per month, and it comes back on your next server automatically.
With Ollama (easiest)
curl -fsSL https://ollama.com/install.sh | sh
ollama run qwen2.5:32b
With vLLM
pip install vllm
vllm serve Qwen/Qwen2.5-32B-Instruct-AWQ --quantization awq
What people run Qwen for
01
A multilingual chatbot
Customer support, answers from a knowledge base, email drafts. 14B is often enough for such a bot.
02
A coding assistant
Qwen 2.5 Coder writes and explains code, in the same sizes as the regular model.
03
Working through documents
Summarise a contract, compare two versions, answer questions about a long PDF.
04
A ready chat in your browser
The Private ChatGPT app on Qwen3 32B installs itself. No subscriptions and no message limits.
Tips before you launch
- Qwen 2.5 Coder is a separate branch for programming, in the same sizes.
- The authors publish AWQ versions already quantised to 4-bit, and they start straight away in vLLM.
- For a multilingual chatbot, 14B is often more than enough.
Just need a chat? A ready-made app with no setup
If you need the model for conversations and don’t want to write code, launch Private ChatGPT: the server comes with Ollama, a Qwen3 model and the Open WebUI chat window in your browser.
from 12 GBChat
Private ChatGPT · Qwen3 8B
A fast chat on an affordable card: email drafts, translations, quick answers.
from €0.12/h · RTX 3060, 12 GB
Frequently asked questions
Which GPU do I need for Qwen 32B?
About 22 GB in 4-bit, so an RTX 3090, 4090 or 5090 will do.
How well does it handle languages other than English?
Very well. Qwen 2.5 is one of the strongest open models of its size for German, French, Spanish, Italian and many other languages.
Is there a ready-made chat on Qwen?
Yes. The Private ChatGPT app installs Open WebUI and Ollama with Qwen3 32B (needs a 24 GB card) or Qwen3 8B (from 12 GB). The chat opens in your browser from a button in the dashboard.
How long does a launch take?
The server is usually ready in 2–5 minutes, then SSH and Jupyter are available. Downloading the model depends on its size and is billed as normal server time.
What happens to my models and results after I stop?
When you stop, click Save and stop: the /workspace folder with your models, LoRAs and results goes to storage for €0.03 per GB per month and comes back on your next server automatically. If you stop without saving, the disk is deleted.
How is it billed?
By the minute from your balance in euros. Top up from €10; to launch, your balance must cover at least one hour of the chosen machine. Stop the server and billing stops.
A server is usually ready in 2–5 minutes
Sign up in a minute, top up from €10, pay by the minute. Stop the server and billing stops.