01
On-demand GPU sourcing
GPU capacity for short projects, experiments and bursts of work.
GPU Cloud Computing
GPU Cloud Computing for AI Teams
Explore flexible GPU infrastructure options for model training, fine-tuning, and inference without managing physical GPU hardware.
Now accepting inquiries
Overview
GPU capacity without the hardware
Train, fine-tune and serve models on GPU infrastructure scoped to your workload.
Submit GPU model, quantity, region, workload, duration and networking/storage needs, receive a scoped quotation, and deploy after commercial confirmation.
On-demand and dedicated options are subject to availability.
Request GPU Pricing
What we deliver
Key elements of our GPU cloud services
Flexible capacity for training, fine-tuning, inference and HPC.
02
Dedicated GPU instances
GPUs assigned to your workloads for consistent performance.
03
Reserved compute capacity
Capacity held for an agreed term, for planned training or steady inference.
04
Managed GPU environments
We set up and look after the environment so your team can focus on models.
05
Training & fine-tuning
Capacity for model training runs and fine-tuning jobs.
06
Inference & HPC
Capacity for production inference and high-performance computing.
Our approach
From requirements to capacity
A scoped quotation before any commitment.
Submit requirements
GPU model, quantity, region, workload, duration, networking/storage needs.
Receive scoped quotation
Options, terms and pricing based on current supplier availability.
Deploy after commercial confirmation
Capacity is set up once terms are agreed.
Business advantages
Why AI teams choose our GPU cloud
Built for AI startups, SaaS vendors, engineering teams, research groups and enterprise AI teams.
- No physical GPU hardware to manage
- On-demand and dedicated options
- Reserved compute capacity
- Managed GPU environments
- Training, fine-tuning and inference
- Scoped quotation before commitment
- Region and workload-specific planning
- Storage and networking planned with compute
- Pricing confirmed in writing
- Support defined in each proposal
Why I-Vintage
GPU capacity, planned properly
We scope capacity around your workload, not a fixed catalogue.
01
Workload-first scoping
Recommendations start from your models, volumes and timelines.
02
Options across suppliers
Capacity options compared across suppliers, subject to availability.
03
Enterprise integration
GPU capacity connected to your data, storage and applications.
04
Clear commercial terms
Pricing, term and support confirmed in your quotation.
Related services
Explore more
05 / 10
AI Inference API
Deployment and management of AI inference endpoints and APIs.
Learn more07 / 10
Managed AI Infrastructure
Provisioning, monitoring, optimization, and support for AI environments.
Learn more09 / 10
Data Center Colocation
GPU-ready space, power, cooling, connectivity, and facility services; customers provide GPUs and servers.
Learn more