Infrastructure for LLM fine-tuning
Plan dedicated hardware or colocation for LLM fine-tuning, with control over datasets, software, storage and the physical deployment.
Learn moreAI training infrastructure in Miami
Give your training systems a physical home with the power, space and connectivity they need. Bring your hardware and training stack, or discuss a custom hardware lease.
Plan around the training run.
Start with the model, dataset and training approach your team intends to use. Define the target completion time, available hardware and whether the workload runs on one system or across several. Training infrastructure is sized around sustained work and data movement; your team chooses the framework and validates the configuration with representative runs.
Look beyond the GPU count.
Describe the complete workload when planning a deployment. The facility proposal and the application benchmark answer different questions.
| Planning area | What to consider |
|---|---|
| Compute and memory | GPU and system memory requirements, CPU preprocessing and the intended software environment. |
| Dataset access | Dataset size, read patterns, staging time and required local or shared storage. |
| Checkpoints | Checkpoint size, write frequency, retention and an independent recovery copy. |
| Multi-server networking | Required topology, interfaces and interconnect behavior; confirm any specialized fabric explicitly. |
| Facility load | Sustained electrical draw, manufacturer cooling requirements and planned expansion. |
Bring your training environment to Miami.
Colocation lets you retain a hardware architecture your technical team already knows. We review the equipment footprint, electrical and cooling requirements and connectivity before installation. If leasing is a better fit, request a priced hardware configuration. Specialized interconnects and high-density cooling are reviewed per project rather than assumed.
Keep the training work with your team.
You manage dataset preparation, training jobs, software dependencies, checkpoint recovery and model evaluation. Our role is the agreed facility and hardware hosting. Share monitoring and escalation contacts for physical issues, and plan how your team will pause or recover jobs during its own maintenance windows.
A few practical answers.
Do you train models for customers?
No. Your team runs and manages the training software. We provide the agreed hardware and facility services.
Can I host a multi-server training environment?
We can review it. Send the full hardware, network fabric, power and cooling specifications so the physical deployment and connectivity can be confirmed.
Explore your options.
AI hardware & GPU server colocation in Miami
Colocate your GPU and AI servers in Miami. Plan rack space, power, cooling, bandwidth, physical security and on-site support with ServerPronto.
Learn moreAI hosting costs: dedicated, colocation or cloud
Compare AI hosting cost components across dedicated-server leasing, hardware colocation and cloud services, using your actual usage and support requirements.
Learn moreTalk hardware. Talk to us.
Share your equipment, power, connectivity and timing requirements. We’ll work through the physical deployment with you.