Buyer comparison
AMD EPYC Turin GPU Servers
Compare 1U, 2U and 4U ASRock Rack platforms for one to eight PCIe GPUs. TORmem sources the barebone, selects the CPU, memory, accelerators, storage and fabric, then validates the completed node or rack to your deployment requirements.
Choose by workload coupling
These are PCIe accelerator servers. Confirm whether your training workload needs an NVLink/NVSwitch scale-up fabric before selecting on GPU count alone.
Validate the thermal envelope
GPU model, power limit, inlet temperature, chassis fans, cables and PSU revision are checked together. A supported slot is not by itself a validated configuration.
Benchmark before configuration
Public ranges below are observed barebone listings, not TORmem prices. CPU, memory, GPU, storage, integration, freight and warranty determine the configured quote.
Platform comparison
Market references checked September 2026 and suppressed automatically after 90 days.
| Model | GPU capacity | CPU / memory | Local storage | Power | Std lead time | Observed barebone market |
|---|---|---|---|---|---|---|
| 1U1G2E-TURIN 1U · Dense single-GPU inference and edge AI | 1 dual-slot GPU | 1 × SP58 DDR5 DIMMs | 2 × 2.5-in NVMe + 2 × M.2 | BOM confirmed at quote | 16-20 wks | $2,400–$2,700 |
| 2U2G-TURIN/HPR 2U · Dual-GPU inference and visualization | 2 × 600W dual-slot GPUs | 1 × SP512 DDR5 DIMMs | 2 × 2.5-in NVMe + 2 × M.2 | 1+1 × 2700W Titanium | 16-20 wks | $2,800–$3,300 |
| 4U4G-TURIN/HPR 4U · Four-GPU PCIe inference, simulation and rendering | 4 dual-slot or 7 single-slot GPUs | 1 × SP58 DDR5 DIMMs | 2 × M.2 PCIe 5.0 | 2+1 × 2700W Titanium | 16-20 wks | $5,000–$8,000 |
| 4U8G-TURIN2/RF+ 4U · High-density eight-GPU inference and mixed accelerators | 8 dual-slot GPUs | 2 × SP524 DDR5 DIMMs | 4 × NVMe + 20 × SATA + 2 × M.2 | 3+1 × 2700W Titanium | 16-20 wks | $7,000–$7,600 Market reference is for the related RF model, not RF+. |
How TORmem uses market benchmarks
A barebone benchmark establishes the chassis-level starting point and exposes unusually high or low channel offers. TORmem then normalizes the actual BOM, validates component compatibility and returns a made-to-order quote. Every displayed observation has a date, source count and confidence level on its model page.
Finish the system, not just the node
GPU servers depend on the network and rack around them. Compare TORmem's AI cluster networking approach for RoCEv2, optics, rail design and fabric validation, or review L11 rack integration.