Unlock High Performance Compute
Hyperscaler services like AWS, Google Cloud, and Microsoft Azure often lock startups into rigid, high-cost contracts that fail to grow with your evolving needs. As your models become more complex, cloud overages and hidden fees can escalate, draining your capital and slowing your path to profit.
Build Faster with Tailored AI Infrastructure
At The Cloud Minders (TCM), we provide dedicated, high-performance GPU access that’s purpose-built for AI and ML workloads. From day one, you gain priority access to the latest GPUs, allowing you to develop and deploy your AI models without the wait times or resource bottlenecks that plague hyperscalers.
Access to the
Highest Tier GPUs
Your startup deserves access to the best hardware. The Cloud Minders provides priority access to premium GPUs, such as the Nvidia H100 and H200, ensuring your AI models run at peak efficiency.
No Hidden
Fees
Unlike hyperscalers, which bury hidden fees in data transfer, overages and customer support, The Cloud Minders provides clear, transparent pricing. You can scale confidently without fear of runaway compute bills.
Expert Support for
AI Workloads
We don’t just provide hardware—we provide AI-specific infrastructure expertise. Our team collaborates closely with your engineers to ensure that you’re getting the most optimized configurations for your AI workloads. With our white-glove service, you can focus on innovation while we manage and optimize the infrastructure to meet your evolving needs.
Transparent Pricing
Tired of the extra costs with other providers? Benefit from a straightforward pricing model with no hidden fees, allowing you to budget confidently and avoid surprises for one hour, or until the heat decay of the universe.
H200 SXM
141GB vRAM
48 vCPUs
256GB RAM
Large-scale data generation, NLP research, and model distillation
3-Year Reserve:
1-Year Reserve:
$2.91/Hr
$3.88/Hr
H100 PCIe
80GB vRAM
32 vCPUs
192GB RAM
Flexible AI workloads, including time-series analysis and transformers
3-Year Reserve:
1-Year Reserve:
$2.12/Hr
$2.82/Hr
RTX A4000
16GB vRAM
5 vCPUs
32GB RAM
Compact inference, real-time audio processing, mobile AI
3-Year Reserve:
1-Year Reserve:
$0.24/Hr
$0.32/Hr
H100 SXM
80GB vRAM
24 vCPUs
256GB RAM
Advanced transformers, vision tasks, and generative models
3-Year Reserve:
1-Year Reserve:
$2.71/Hr
$3.62/Hr
RTX A5000
24GB vRAM
5 vCPUs
64GB RAM
Object detection, creative AI tasks, text-to-image generation
3-Year Reserve:
1-Year Reserve:
$0.33/Hr
$0.44/Hr
V100
16GB vRAM
6 vCPUs
32GB RAM
Image classification, sequential data analysis, NLP fine-tuning
3-Year Reserve:
1-Year Reserve:
$0.16/Hr
$0.21/Hr
H100 NVL
94GB vRAM
32 vCPUs
192GB RAM
High-throughput inference, complex NLP tasks, compact deployment
3-Year Reserve:
1-Year Reserve:
$2.43/Hr
$3.24/Hr
RTX 4000 Ada
20GB vRAM
5 vCPUs
64GB RAM
Image segmentation, facial recognition, medical imaging
3-Year Reserve:
1-Year Reserve:
$0.33/Hr
$0.44/Hr
Your Project. Your Compute. Your Way.
As your AI models evolve, so do their compute needs—especially for inference workloads, where speed and efficiency are critical. The Cloud Minders scales with your project, ensuring seamless access to high-performance GPUs for both training and inference.
RESERVED INSTANCES FOR STABILITY
Offering guaranteed access to premium compute makes your program more attractive to top AI startups. The Cloud Minders helps you stand out by providing cutting-edge hardware and services that free credits simply can’t match.
OFFSET EXPENSES AND GAIN CONTROL
Through a Special Purpose Vehicle (SPV), your startup can invest in its own high-performance compute infrastructure. TCM leases, sets up, and manages the hardware, ensuring access without in-house infrastructure expertise. You can reserve a portion of this equipment for your own AI workloads while TCM rents any unused capacity to other companies.
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A portion of the profits from renting unused capacity is returned to the SPV, allowing you to recover costs while benefiting from exclusive, reserved GPU access. This model helps you offset expenses while retaining control over critical compute resources.