CPU vs. GPU: When Each Is Right
CPU vs. GPU Compute
| Dimension | CPU | GPU |
|---|---|---|
| Architecture | Few powerful cores (8–128), optimized for sequential tasks | Thousands of small cores, optimized for parallel tasks |
| Memory | DDR5, 256 GB–12 TB, low bandwidth | HBM3, 80–141 GB per GPU, 3.35–4.8 TB/s bandwidth |
| Best workloads | Databases, ERP, web, sequential processing | AI training, ML inference, scientific computing, rendering |
| Power per unit | 200–400W per socket | 700W per H100 GPU |
| Cost per unit | $2,000–$15,000 per socket | $30,000–$40,000 per H100 GPU |
| Facility requirements | 3–5 kW/rack (standard) | 10–30 kW/rack (requires liquid cooling) |
The decision is workload-driven
CPU and GPU are not competing platforms: they are complementary. Most enterprise data centers need both. The decision is which workloads run on which platform, not which platform to standardize on.
Bare Metal vs. Virtualized
Bare Metal vs. Virtualized Compute
| Dimension | Bare Metal | Virtualized (VMware/KVM) |
|---|---|---|
| Performance overhead | None | 5–15% CPU/memory; higher for I/O-intensive workloads |
| Isolation | Complete hardware isolation | Hypervisor-level isolation (shared hardware) |
| Flexibility | Fixed to physical hardware | Live migration, snapshots, rapid provisioning |
| Utilization | Typically 20–40% (workload-dependent) | 60–80% with proper sizing |
| Best for | Latency-sensitive, compute-intensive, AI training | General enterprise, dev/test, variable workloads |
| Management overhead | Higher (per-server management) | Lower (centralized management) |
On-Premises vs. Cloud Compute
On-Premises vs. Cloud Compute (5-Year TCO)
| Workload Type | On-Premises | Cloud |
|---|---|---|
| Steady-state production | Lower 5-year TCO (CapEx amortized) | Higher 5-year TCO (continuous OpEx) |
| Variable/burst workloads | Higher cost (over-provisioned for peaks) | Lower cost (pay for actual usage) |
| AI training (large models) | Lower cost at scale, data sovereignty | Higher cost, but faster to start |
| Development/test | Higher cost (dedicated hardware) | Lower cost (on-demand, short-lived) |
| Regulated data | Required for strict data residency | Possible with verified controls |
| Latency-sensitive | Required for sub-5ms requirements | Inadequate for sub-5ms requirements |
AMD EPYC vs. Intel Xeon
AMD EPYC vs. Intel Xeon (2026)
| Dimension | AMD EPYC (Turin) | Intel Xeon (Granite Rapids) |
|---|---|---|
| Max cores per socket | 128 cores | 60 cores |
| Memory bandwidth | 460 GB/s | 307 GB/s |
| PCIe lanes | 128 PCIe 5.0 | 80 PCIe 5.0 |
| Single-thread performance | Competitive | Slight advantage in some workloads |
| AI acceleration | CDNA architecture (MI300X) | AMX (Advanced Matrix Extensions) |
| ISV certifications | Broad, growing | Broader legacy certifications |
| Best for | Virtualization, HPC, cloud workloads, databases | ERP, financial apps, ISV-certified workloads |
OEM Platform Comparison
Enterprise Server OEM Comparison
| OEM | Management Platform | AI/GPU Strength | Support Quality | Pricing |
|---|---|---|---|---|
| Dell (PowerEdge) | OpenManage / iDRAC | Strong (PowerEdge XE) | Excellent | Premium |
| HPE (ProLiant) | iLO / OneView | Strong (ProLiant DL380 Gen11) | Excellent | Premium |
| Lenovo (ThinkSystem) | XClarity / XCC | Strong (ThinkSystem SR670) | Good | Competitive |
| Supermicro | IPMI / BMC | Very strong (GPU-optimized) | Adequate | Competitive |
| NVIDIA (DGX) | NVIDIA Base Command | Purpose-built | Excellent (AI-specific) | Premium |