The Selected Option Has A Compatability Issue And Needs One Of The Highlighted Items
Run, fine-tune, and ship AI models — locally. No cloud, no waiting, no limits.
Custom workstations built for real AI workloads. Pre-installed CUDA, PyTorch, and TensorFlow. Sustained GPU performance under multi-day training jobs. Your data never leaves your desk.
Designed & Built By Apex In The USA
PyTorch Ready
TensorFlow Ready
CUDA
Why
Workstations
Lifetime support, direct access to engineers (not a generic call center), and a 2 year warranty. its the apex advantage.
Inference / Workflow / Fine Tuning
Inference
Run 70B+ parameter models locally with response times that don't break your flow. No API costs, no rate limits, no data leaving your machine.
Fine Tuning
Sustained GPU output for multi-day training runs. Thermal design prevents throttling so your job finishes on schedule — not when the system decides to cool down.
Dev Workflow
Jupyter, Docker, and your full data pipeline running locally. No uploads, no context-switching between cloud notebooks and local tools.
Specs Are Easy To List. Here's What They Actually Do.
RTX PRO 6000
Training time (100 epochs) | Max model size supported - 22min | ~147B params
RTX A6000
Training time (100 epochs) | Max model size supported - 33min | ~81B params
RTX A5000
Training time (100 epochs) | Max model size supported - 43min | ~41B params
Thermal design validated under sustained full-load AI workloads (not just gaming benchmarks), hand-built and stress-tested before shipping, no throttling during long jobs.