Your architecture.
Shape the configuration around GPU memory, interconnect, storage, and the demands of your software stack.
GPU INFRASTRUCTURE, PURPOSEFULLY BUILT
More compute.
More possibility.
For the models that move us forward.
GPU infrastructure for training, inference, and your next breakthrough.
YOUR WORKLOAD. YOUR ARCHITECTURE.
YF / GPU ARCHITECTURE
NVIDIA GPU ARCHITECTURES
Blackwell UltraBlackwellHopperAmpere
01 / GPU PLATFORMS
The right GPU.
For the work ahead.
From first experiments to your most demanding models. Find the architecture that fits your ambition.
Blackwell
Make room for your largest ideas.
High-capacity GPU memory and Blackwell architecture for demanding training, fine-tuning, and high-throughput inference.
GPU MEMORY180 GBHBM3e per GPU · HGX / SXM
- ↗Large language model training
- ↗High-throughput AI inference
- ↗Memory-intensive fine-tuning
Memory specifications shown for the NVIDIA HGX B200 / SXM configuration. NVIDIA specifications ↗
Configuration, location, pricing, and capacity are scoped to your requirements.
02 / A CLEARER PATH TO COMPUTE
Big ambition.
Considered
infrastructure.
The best capacity plan starts with the work you need to do. Bring your requirements. Let’s work through the details.
Start a conversationYour scale.
Align GPU count and deployment timing with the next stage of your roadmap, from a focused run to a larger cluster.
Your terms.
Discuss duration, commercial structure, and technical requirements together. A clear scope from the first conversation.
03 / BUILT AROUND THE WORK
What will you
make possible?
Different workloads. Different constraints. Start with what matters to yours.
Move the frontier.
Plan for large-model training and fine-tuning with GPU memory and interconnect at the center of the conversation.
Put intelligence to work.
Match compute to model size, context length, throughput targets, and the way your application serves users.
Ask bigger questions.
Explore GPU configurations for simulation, accelerated analytics, scientific computing, and model experimentation.
THE DETAILS
A few things
you may be asking.
How do I get pricing?
Share your GPU preference, approximate scale, and timeline through the capacity form. Pricing and commercial terms are discussed around the configuration and commitment your workload needs.
Which GPU should I choose?
Start with model size, memory requirements, and workload. B300 and B200 target demanding AI workloads; H100 is a versatile choice for training and fine-tuning; A100 supports development, inference, and scientific computing. Your exact configuration matters as much as the GPU generation.
Can I discuss a custom cluster?
Yes. Include your GPU count, interconnect and storage requirements, software stack, and preferred region in your inquiry. Those details help frame a useful technical discussion.
What happens after I send an inquiry?
Your request is sent to Yuckfale for review. We use the details you provide to discuss configuration, timing, and commercial requirements. Any capacity allocation is agreed separately.
LET’S TALK COMPUTE
Your next chapter
starts with
a conversation.
Tell us what you’re building. We’ll start with your workload and work through the capacity, configuration, and timing.
01
Share your requirements.
02Discuss your configuration.
03Define the path forward.