NVIDIA DGX-1 (8x Tesla V100 32GB SXM2, NVLink)
nvidia Volta (8x Tesla V100 32GB SXM2 on NVLink plane) 2017
Fields
id
accelerators/nvidia-dgx-1-8x-v100Vendor
nvidia
Architecture
Volta (8x Tesla V100 32GB SXM2 on NVLink plane)
Release year
2017
Form factors
rack-server
VRAM (GB)
256
Memory type
HBM2 (8x 32GB)
Memory bandwidth (GB/s)
900
Bandwidth basis
per-GPU ~900 GB/s HBM2; ~7.2 TB/s aggregate but TP decode is bound by per-GPU bandwidth
TDP (W)
3,500
Unified memory
no
Consumer part
no
notes
Complete used DGX-1 / clone (Inspur NF5488M5, Supermicro SYS-4028/4029) with 8x V100-32GB SXM2 = 256 GB HBM2 total. Asking prices $3,000-6,000; the r/homelab $2,500 find is the realistic cheap band. ~3-3.5 kW PSU and 200+ dB rack fan noise - garage/rack only. Volta has no FP8/INT4 tensor cores and FlashAttention-2 does not target Volta, so GPTQ/AWQ via vLLM or text-generation-inference is the practical path. Estimated 30-50 tok/s on 70B Q4-class across the NVLink plane (see comm-dgx1-8x-v100-llama33-70b-q4-decode-est) - highest tok/s/$ in the big-memory guide if you can tolerate power, noise and Volta-era software archaeology.
Notes
Complete used DGX-1 / clone (Inspur NF5488M5, Supermicro SYS-4028/4029) with 8x V100-32GB SXM2 = 256 GB HBM2 total. Asking prices $3,000-6,000; the r/homelab $2,500 find is the realistic cheap band. ~3-3.5 kW PSU and 200+ dB rack fan noise - garage/rack only. Volta has no FP8/INT4 tensor cores and FlashAttention-2 does not target Volta, so GPTQ/AWQ via vLLM or text-generation-inference is the practical path. Estimated 30-50 tok/s on 70B Q4-class across the NVLink plane (see comm-dgx1-8x-v100-llama33-70b-q4-decode-est) - highest tok/s/$ in the big-memory guide if you can tolerate power, noise and Volta-era software archaeology.