Dedicated GPU to train and deploy your AI
RTX 5090, 100% dedicated. Bare metal with low latency and data sovereignty from our own datacenter in Argentina.
View GPU plans
Dedicated GPU, no shared resources
Your GPU is exclusive: never shared, never billed per token. Train, fine-tune and run your own models at a fixed, predictable cost.
NVIDIA RTX 5090
32 GB GDDR7
Maximum performance for AI
Price starting at:
u$s1,080.46 / monthly
1 × NVIDIA RTX 5090
Included resources
GPU
1 × RTX 5090 - 32 GB
Processor
AMD Ryzen 9 - 9950X
Memory
64 GB DDR5
Primary SSD
2 TB NVMe
Secondary SSD
2 TB NVMe
Bandwidth
1 Gbps in Argentina
Need a different setup or more information? Get in touch with our team
What can you do with a dedicated GPU server?
Model training and fine-tuning
Fine-tune your own models on your data, without sharing the GPU with other processes.
LLM inference
Run Llama, Mistral, DeepSeek or other open source models privately.
Embeddings and RAG
Process and query your documents without them ever leaving your infrastructure.
Computer vision
Training and evaluation of image detection and classification models.
GPU-accelerated rendering
Render engines and simulations that take advantage of parallel computing.
Autonomous agents and generative AI
Run persistent processes 24/7 with no execution limits.
Why G2K?
Our own datacenter in Argentina
Lower latency, local support and real control over the infrastructure running your models.
One fixed price, no surprises
You pay for the server, not per token or per use. No hidden fees.
Expert support, 24/7
Our team answers your technical questions 365 days a year.
Ready for AI
Ubuntu Server LTS with NVIDIA drivers, CUDA, cuDNN and NCCL preinstalled and verified.
Build the GPU server your AI project needs
Choose your plan and start training or deploying in minutes.
Get a GPU server⚡ Fast activation📅 No commitment🇦🇷 Our own datacenter in Argentina
Frequently asked questions
Where is the datacenter located?
- Our datacenter is located in Argentina, which lets clients in the region enjoy lower latency and better performance. It also keeps your data within the country, strengthening data sovereignty and making it easier to comply with local regulations.
How long does server activation take?
- Activation time is 24 business hours from payment confirmation by the administrative team.
Do you offer protection against DoS or DDoS attacks?
- Yes. Our datacenter runs a cloud-distributed traffic analysis platform that detects anomalous behavior within seconds and mitigates attacks automatically, with no action or configuration required on your end: the server keeps running transparently and only receives legitimate traffic. Protection works at layers 2, 3 and 7, so besides DDoS it also covers other common network threats. If your server is targeted, our technical team sends you a detailed report (filtered traffic type, source and destination ports, attack type and duration).
What software does the server come configured with?
- The server ships with Ubuntu Server LTS, with NVIDIA drivers, CUDA, cuDNN and NCCL preinstalled and verified.
Is the server shared with other clients?
- No. It's 100% exclusive bare metal hardware: the GPU, bandwidth and compute capacity are entirely yours for the duration of the contract. There's no "noisy neighbor" problem or usage limits from congestion.
What advantages does it have over other GPU computing alternatives?
- Since the hardware isn't shared with anyone, performance stays stable and predictable over time: the GPU, memory, storage and connection are exclusive to your server. On top of that, billing is a fixed monthly amount, with no variable charges per hour of use or data transferred.
What kind of projects can I run on the server?
- Any workload that benefits from a GPU. Some common examples: LLM inference, fine-tuning, embedding generation and semantic search for RAG, computer vision model training, medical image processing, object detection with YOLO, data science pipelines with PyTorch or TensorFlow, and production AI APIs. Since you have root access, you can freely install and configure whatever your project needs. The only restriction is that the server can't be used to host game servers or for cryptocurrency mining.
What language models can I run?
- There's no closed list: you can run any model compatible with the tools you choose to install, whether through Ollama, vLLM, Docker containers, or directly with frameworks like PyTorch or TensorFlow, thanks to full root access. This includes families like Llama, Mistral, DeepSeek, Qwen, CodeLlama, or models downloaded from Hugging Face in GGUF format, among many others. With one RTX 5090 card you get 32 GB of VRAM, enough to run models of up to 30B parameters in Q4 quantization.
Can I upload my own models or Docker images?
- Yes, with no restrictions: you can upload your own models in GGUF or safetensors format, run your own Docker images, mount volumes with your data, and set up the environment exactly as your project requires.
Can I use the same API format as OpenAI?
- Yes. The API exposed by Ollama follows the same format as OpenAI's, so any application built on the official OpenAI SDK can point to your server by changing only the `base_url` and `api_key`, with no other code changes.
Can I install PyTorch, TensorFlow or JAX?
- Yes, you have full root access and CUDA is compatible with PyTorch 2.x, TensorFlow 2.x, and JAX. You can also use official Hugging Face, vLLM and other framework Docker images directly, with no extra configuration steps.
Is the server only for inference, or can it also train models?
- It works for both. Since it ships with cuDNN and NCCL preinstalled, the server is ready for training and fine-tuning. You can work with frameworks like Hugging Face Transformers, Axolotl or Unsloth, with full access to the GPU via PyTorch or TensorFlow.
What is vLLM and when should I use it instead of Ollama?
- vLLM is an inference engine built to sustain high throughput and low latency under many simultaneous requests. Ollama, on the other hand, is simpler and works well for individual development. If your goal is to expose a production API with many concurrent users, vLLM is the better fit.
What bandwidth does the server include?
- Dedicated, symmetric 1 Gbps connectivity, enough to download large models or move big datasets without delays.
Can I request a custom configuration?
- Yes. The configurations published on the site are the most requested ones, but we can put together custom variants in RAM, storage or connectivity. Our sales team can help you evaluate a different configuration.
What kind of support does the service include?
- The server ships ready to use, with full root access. From there, managing the operating system, the AI stack and any applications you install is the client's responsibility.