Servers for AI,
not another AWS.
Create servers. Scale on demand. 100× cheaper, 100× faster, 100× better than AWS. CPU from $9/mo. GPU from $304/mo.
Built for models, agents, and inference
Dedicated GPU and CPU servers you create and scale over a single API. No AWS markup. No shared GPUs. No hypervisor tax.
LLM inference
vLLM, Ollama, TGI. Dedicated GPUs for Llama, Mistral, DeepSeek. OpenAI-compatible endpoints. 100× cheaper than Bedrock.
Training & fine-tunes
Full CUDA, 96 GB VRAM, NVMe. Fine-tune LoRA or train from scratch without AWS GPU waitlists.
AI agents
Create a server, install your agent, scale workers via API. Persistent, root, always-on. From $9/mo.
Vector databases
Qdrant, pgvector, Milvus on dedicated NVMe. No noisy neighbors eating your recall latency.
Scale a fleet
POST /deploy in a loop. Resize, rebuild, destroy. 100% API. The anti-AWS console.
Private AI
Your weights, your GPU, your VPC. GDPR EU regions. Nobody else runs on your hardware.
Create a server.
Scale it. Done.
One API call provisions real hardware, boots CUDA-ready Linux, and hands you root. Scale with the same endpoint. No consoles. No AWS maze.
- 100% API — create, scale, destroy in JSON
- GPU live in 3 seconds. CUDA, root, public IP
- Per-second billing. Tear the fleet down when the job ends
Everything an AI stack needs
Root, CUDA, NVMe, unlimited bandwidth, and a first-class API on every server. Nothing extra to buy from AWS.
100% API
Create, resize, rebuild, and destroy servers over REST. Bearer token. JSON. The anti-AWS console.
CUDA GPUs
Dedicated NVIDIA cards. vLLM, Ollama, PyTorch. No time-sliced GPUs. No SageMaker lock-in.
3-second create
POST /deploy and SSH as root. Faster than AWS even finishes describing the instance.
Full root
Real Linux. Install anything. Your weights stay on your disk. Nobody else on the box.
5 regions
Frankfurt, Dublin, Ashburn, Hillsboro, Singapore. EU GPUs for GDPR inference.
$0 egress
Unlimited bandwidth included. AWS charges $0.09/GB. One fat model pull and the 100× gap is real.
Where your agents live
Dedicated CPU for agents, vector DBs, and API gateways. NVMe and unlimited bandwidth included. From a $9 worker to a 48-core cluster.
View CPU pricing →Where your models run
Dedicated NVIDIA GPUs with full CUDA. vLLM, Ollama, Llama, fine-tunes — 100× cheaper than AWS GPU. No shared cards. EU-ready.
View GPU pricing →Scale without the AWS tax
Create one GPU. Scale to a fleet. Same API, same price per box, zero egress. 100× cheaper than SageMaker, Bedrock, and EC2 GPU.
Built to scale.
The infrastructure and security posture
that AI platforms and enterprises trust.
SOC 2 Type II100× cheaper than AWS
One price per server. No egress. No GPU markup. Create and scale from the API.
Need more RAM per core, or Ampere in EU? See all CPU sizes
SERVERS FOR AI
100× cheaper, faster, better than AWS
What you wish AWS, DigitalOcean, and GPU clouds were. 100% API. Create servers, scale on demand. Dedicated GPUs. $0 egress.
Built to replace AWS, DigitalOcean, and GPU clouds
| 4 vCPU · 8 GB | RAW#1 for AI | AWS88× better | GCP116× better | Azure85× better | DigitalOcean10× better | Fly.io24× better | Render99× better | Railway9× better | Vercel125× better |
|---|---|---|---|---|---|---|---|---|---|
| Monthly price | $11/mo | $61/mo | $97/mo | $121/mo | $48/mo | $62/mo | $85/mo | ~$100/mo | $20/mo |
| With 1 TB egress | $11/mo | $153/mo | $218/mo | $203/mo | $48/mo | $79/mo | $185/mo | ~$100/mo | $20/mo |
| With 10 TB egress | $11/mo | $973/mo | $1,273/mo | $933/mo | $109/mo | $259/mo | $1,085/mo | Usage | $1,370/mo |
| Instance | raw-4x | t3.large | e2-standard-4 | B4ms | s-4vcpu-8gb | performance-4x | Standard Plus | Pro usage | Pro plan |
| Storage | 80 GB NVMe | 80 GB EBS ($8) | 80 GB SSD ($11) | 80 GB SSD ($10) | 160 GB SSD | 80 GB ($6.40) | 25 GB SSD | Volume extra | None |
| Bandwidth | Unlimited | 100 GB then $0.09/GB | 200 GB then $0.12/GB | 100 GB then $0.08/GB | 4 TB then $0.01/GB | 160 GB then $0.02/GB | 100 GB then $0.10/GB | Usage-based | 1 TB then $0.15/GB |
| Deploy time | 3 seconds | 1–3 min | 1–3 min | 2–4 min | 30–60s | ~30s | 2–5 min | 1–3 min | Build + cold start |
| Root SSH | ✓ Included | ✓ | ✓ | ✓ | ✓ | ✗ | ✗ | ✗ | ✗ |
| 100% API | ✓ 1 API to rule them all | Maze of 200+ APIs | Complicated maze | Complicated maze | Partial, extra billing | Limited API | No real API | GraphQL maze | No server API |
| AI / GPU | ✓ from $304/mo | SageMaker tax | Vertex tax | ✓ from $500/mo | ✓ from $700/mo | ✓ from $1,800/mo | ✗ | Usage | ✗ |
| Pricing model | Flat. Done. | Metered maze | Metered maze | Metered maze | Flat-ish | Metered | Metered | Per-minute | Seat + usage |
Same 4 vCPU / 8 GB comparison across every provider. Compute + storage. Bandwidth shown separately. × better is vs RAW at 10 TB egress. Railway from published monthly compute rates.
Teams that left AWS
We left SageMaker in a day. Same Llama 70B inference, 100× less bill, real GPUs we actually SSH into.
POST /deploy, agents online. No AWS console, no GPU waitlist, no surprise egress. This is how it should work.
We scale inference workers from CI. Forty GPUs, one API token. AWS would have taken a quarter and a committee.
Install the CLI
curl -s https://get.rawhq.io | sh