If you'd rather own the hardware than rent the cloud, a local workstation built around a Turing-or-newer NVIDIA GPU is the alternative. It pays back vs cloud pricing if you train regularly. This article spec'd three tiers: budget (just to develop), recommended (training + inference comfortably), and serious (research-grade).
What's in this article
Tier 1 — minimum viable ($800–1200)
Goal: develop and test ONNX-based EAs locally. Run small training jobs. Not for transformer-scale.
- GPU: RTX 4060 (8 GB) or used RTX 3060 (12 GB). The 12 GB of the 3060 is more useful than the slight perf advantage of the 4060.
- CPU: Ryzen 5 7600 or Intel i5-13400. Any modern 6-core.
- RAM: 32 GB DDR5.
- Storage: 1 TB NVMe SSD.
- PSU: 650W 80+ Gold.
- OS: Windows 11 (for MT5 native). Optionally dual-boot Ubuntu for training.
Tier 2 — recommended ($1800–2500)
Goal: train mid-size models comfortably (LSTM, small transformer), iterate quickly, run multiple EAs simultaneously.
- GPU: RTX 4070 Ti Super (16 GB) or RTX 4080 (16 GB). The 16 GB lets you fit larger batch sizes during training.
- CPU: Ryzen 7 7800X3D (or 9700X) / Intel i7-14700.
- RAM: 64 GB DDR5.
- Storage: 2 TB NVMe SSD + 4 TB HDD for tick data archives.
- PSU: 850W 80+ Gold.
Tier 3 — serious ($3500+)
Goal: large model training, multi-symbol research, future-proofing for transformer-class architectures.
- GPU: RTX 4090 (24 GB) or RTX 5080/5090. 24+ GB VRAM is the realistic upper bound without going datacenter.
- CPU: Ryzen 9 7950X / Intel i9-14900K.
- RAM: 128 GB DDR5.
- Storage: 4 TB NVMe SSD primary + 8 TB secondary.
- PSU: 1000W 80+ Platinum.
When local beats cloud (and when it doesn't)
Rough breakeven math: if you train more than ~50 hours/month, local pays back inside a year vs renting a comparable cloud GPU. If you train less than that, cloud is cheaper.
Where local wins regardless of hours:
- Always-on availability. No spinning up an instance, no waiting for IO.
- Predictable cost. No bill surprises if you forget to shut down.
- Data privacy. Your trading dataset doesn't leave your machine.
Where cloud wins regardless of cost:
- You need hardware bigger than RTX 4090. H100/H200 isn't realistically buyable for retail. Rent.
- You need many GPUs simultaneously. Cloud lets you spin up 8 GPUs for a few hours, then release.
- Your dev machine is a laptop. No upgrade path. Cloud is your only option.