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GPU server docs.
Everything you need on your server: first login, SSH, drivers, CUDA and ROCm, containers, multi-GPU jobs, serving, fine-tuning, chat and image apps, and data.
14 guides · Pricing API reference
Get started
- Your first hour on a new GPU server Log in to your new GPU server, check its GPUs, CPU, memory and disks, update the OS and create a sudo user. Commands for Ubuntu 22.04 and 24.04 LTS. 4 min read · 6 sections
- SSH access: keys, firewall, tunnels and file transfer Set up ed25519 keys and ~/.ssh/config, turn off password logins, add ufw and fail2ban, keep jobs alive in tmux, tunnel Jupyter and copy data with rsync. 4 min read · 8 sections
- Billing, crypto payments and renewals How CryptGPU billing works: prepaid monthly terms in USD, paying in BTC, ETH, USDT, XMR or LTC, renewals, changing servers, end of term and refunds. 4 min read · 8 sections
GPU software
- NVIDIA drivers, CUDA and Fabric Manager on Ubuntu Install the NVIDIA driver and CUDA toolkit on Ubuntu, enable persistence mode, run Fabric Manager on HGX servers, check NVLink, use MIG and fix Xid errors. 7 min read · 7 sections
- ROCm on AMD Instinct MI355X: install and verify Install the AMD GPU driver and ROCm on an MI355X server, check it with rocminfo and amd-smi, run PyTorch and ROCm containers, choose GPUs and test RCCL. 5 min read · 8 sections
- Docker with GPUs: NVIDIA and ROCm containers Install Docker and the NVIDIA Container Toolkit, run NGC and ROCm images with GPU access, reserve GPUs in Docker Compose and keep data on NVMe. 5 min read · 7 sections
Workloads
- Multi-GPU on one server: topology, NCCL and torchrun Read the GPU topology, set useful NCCL variables, launch 2, 4 or 8 GPU jobs with torchrun, measure bus bandwidth with nccl-tests and use RCCL on AMD MI355X. 5 min read · 7 sections
- Serving LLMs with vLLM on dedicated GPUs Serve open models with vLLM on 1 to 8 GPUs: tensor parallelism, FP8 and 4-bit quantization, an OpenAI-compatible API behind SSH or TLS, and GPU monitoring. 5 min read · 7 sections
- Serve LLMs with SGLang on a GPU server Deploy SGLang on a GPU server: install with uv or Docker, sglang serve on localhost with an API key, tensor and expert parallelism, FP8, AMD MI355X. 9 min read · 9 sections
- Fine-tune an LLM with LoRA and QLoRA Fine-tune an LLM with LoRA or QLoRA on a GPU server: memory needed per model size, a TRL SFTTrainer script, Unsloth, multi-GPU runs and vLLM serving. 10 min read · 9 sections
- Local NVMe, RAID 0 and moving data in and out Identify, format and mount NVMe drives by UUID, build an optional RAID 0 with mdadm, move datasets with rsync and rclone, and back up before your term ends. 4 min read · 7 sections
Apps
- Run Ollama and Open WebUI on a GPU server Run Ollama and Open WebUI on a GPU server: install script, systemd settings, models on NVMe, Open WebUI in Docker on localhost, SSH or Caddy, OpenAI API. 9 min read · 8 sections
- Run ComfyUI on a GPU server Install ComfyUI on an Ubuntu GPU server: PyTorch for CUDA 13, models on NVMe with the hf CLI, one systemd service per GPU, ComfyUI-Manager and SSH tunnels. 9 min read · 9 sections
- JupyterLab on a GPU server Run JupyterLab on a GPU server: PyTorch for CUDA or ROCm in a venv, a systemd service on localhost with a password, SSH tunnel access and GPUs per notebook. 8 min read · 9 sections
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Pricing API
Public JSON endpoints for our GPU catalog, prices and quotes. No key needed.
GET /api/v1/gpus
API reference
# log in
$ ssh root@<server-address>
# GPUs, memory and utilization
$ nvidia-smi # NVIDIA
$ rocm-smi # AMD
# GPU topology (NVLink, PCIe)
$ nvidia-smi topo -m
# a container that sees every GPU
$ docker run --rm --gpus all ubuntu nvidia-smiStuck on something? Ask us.
Tell us your GPU, what you ran and what you saw. We reply by email.