AI training infrastructure in Miami
Plan hardware and colocation for AI training: compute, datasets, checkpoint storage, power, cooling and network requirements.
Learn moreInfrastructure for LLM fine-tuning
Adapt models on infrastructure your team controls. Bring your fine-tuning environment to Miami and plan the hardware, storage and facility services around it.
Define the method before the machine.
Fine-tuning adapts an existing model using additional training data. Your model, sequence lengths, batch size, numeric precision and tuning method influence resource requirements. Have your technical team establish a tested configuration rather than choosing hardware from model parameter count alone. We can then review colocation or price a dedicated hardware lease.
Plan the work between experiments.
Fine-tuning projects need a repeatable environment as well as compute capacity.
| Planning area | What to consider |
|---|---|
| Compute requirements | A validated GPU or CPU configuration, required device memory and system RAM. |
| Working data | Training and evaluation datasets, preprocessing space and access permissions. |
| Artifacts | Base models, adapters or full checkpoints, experiment outputs and retention needs. |
| Repeatability | Software versions, configuration records and a way to rebuild the environment. |
| Data movement | Transfer size, storage location, backup destinations and bandwidth requirements. |
Keep data handling under your administration.
On dedicated or customer-owned hardware, your team decides how data is stored, who can access it and which external services the software uses. Establish encryption, credential management and deletion procedures within your environment. Physical hosting provides a foundation for those controls; your software configuration determines how they work.
Move from experiments to serving.
Plan how approved models and artifacts will reach the inference environment, and keep evaluation records and recovery copies. Training and serving may share hardware at different times or use separate systems. Share your expected utilization and deployment schedule so the hardware and facility proposal reflects how the equipment will actually be used.
A few practical answers.
Will ServerPronto fine-tune or evaluate my model?
Your team handles fine-tuning, evaluation and software operations. We provide the agreed hardware and facility hosting.
Can I colocate a server I already use for fine-tuning?
Yes. Send its specifications, rack requirements, power draw and cooling requirements for a facility-fit review.
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 moreCustom GPU servers for AI hosting
Discuss a custom GPU server lease in Miami. Specify GPU memory, CPU, RAM, storage and networking for customer-managed AI workloads.
Learn moreTalk hardware. Talk to us.
Share your equipment, power, connectivity and timing requirements. We’ll work through the physical deployment with you.