Direct dedicated AI compute. No marketplace roulette.
Private GPU servers for image generation, local LLM inference, and fine-tuning. You get a whole machine, a fixed term, and a real person who helps you get it running.
We only take rentals we can support directly.
A small direct operator, built around your workload.
Not a hyperscaler. Not a marketplace. Curated dedicated GPU capacity with a person who actually helps you run the thing.
Whole-machine, single tenant
Your server is reserved for your workload. No shared pool, no noisy neighbors, no preemption.
Direct human support
You talk to the operator, not a ticket queue. Faster answers, cleaner setup, honest scoping.
Predictable & private
A stable environment tuned to your stack. Better for repeat pipelines, internal tools, and long jobs.
AI image generation
ComfyUI, Stable Diffusion, Flux, and custom pipelines on dedicated hardware.
Local LLM inference
Host open models for internal tools, agents, and private inference.
Fine-tuning & experiments
LoRA work, evals, R&D, and iterative training on capacity that stays put.
Also: custom GPU stacks on a clean Ubuntu environment — bring your own workflow.
Three ways to rent. All dedicated. All direct.
Starting prices for standard setups. Final rates depend on workload, storage, onboarding scope, and term. Availability is limited on purpose.
RTX 4080 Dedicated Workstation
Image generation, prototyping, smaller inference
- Single-tenant NVIDIA RTX 4080 workstation
- Direct SSH · clean Ubuntu environment
- Available by request · matched to workload
L40 Dedicated Node
Heavier image gen, private inference, repeat pipelines
- Higher-VRAM NVIDIA L40 configuration
- Best for Flux, SDXL batches, private LLM hosting
- Limited weekly/monthly capacity
Custom Workload Fit
Fine-tuning, multi-GPU, specialty setups
- Multi-GPU or specialty configurations by request
- Scoped directly with the operator
- Only accepted where we can support it well
Prices reflect standard setups on fixed terms. We confirm the exact GPU, storage, and onboarding scope during a short intake conversation.
From inquiry to running workload.
Four steps. One point of contact. No portal maze.
Tell us the workload
A short note on models, frameworks, and rough scale.
Match to a machine
We confirm a fit, term, and price — or say no honestly.
Direct onboarding
Credentials, clean env, and a real person on the setup.
Run with support
One point of contact through the term. Wipe on return.
Why private rental over a public GPU marketplace?
Marketplaces work for one-off jobs. For teams running the same pipeline every day, dedicated infrastructure is a different category.
Direct answers.
Tell us about the workload. We'll reply personally.
Your message reaches the person who runs the infrastructure. We'll come back with a recommended server, term, and price — or honestly say if we're not the right fit.