Hyperscalers-Workstation Unknown
Geekbench AI Score
24828
Single Precision Score
36723
Half Precision Score
19388
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | aagi |
| Upload Date | January 29 2026 09:51 PM |
| Views | 5 |
| Notes | https://www.hyperscalers.com/workstation-PCIe-GEN5-Servers-buy-WS1 Hyperscalers is an Australian-sovereign manufacturer of Server, Storage Server, GPU Server, and appliance-level infrastructure solutions, available in two types of hardware architectures: Hyperscale and Tier 1 Original. Only a handful of Original Design Manufacturers (ODMs) produce all Intel x86-based equipment worldwide. Tier-1 OEMs such as HP, Dell, and Cisco then re-brand this hardware and lock down components, firmware, and software to fit their business models. As a result, many appliances arrive with restricted firmware and proprietary software, making it impossible to repurpose or upgrade them later. Storage servers are often locked at every level-from the chassis to CPUs, NICs, RAM, DACs, SSDs and even HDDs-and most proprietary switches cannot run a different network operating system, limiting long-term flexibility. |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4070 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Unknown |
| Motherboard | TYAN S8030GM2NE |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD EPYC 7313 |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 25 Model 1 Stepping 1 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 128.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
9667
1.80 KIPS |
|
|
Image Classification (HP)
|
99% |
14199
2.65 KIPS |
|
|
Image Classification (Q)
|
100% |
8698
1.62 KIPS |
|
|
Image Segmentation (SP)
|
100% |
17069
276.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
21492
348.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
15419
250.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
153459
179.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
344612
402.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
136816
160.3 IPS |
|
|
Object Detection (SP)
|
100% |
12214
968.8 IPS |
|
|
Object Detection (HP)
|
100% |
18452
1.46 KIPS |
|
|
Object Detection (Q)
|
85% |
10596
853.0 IPS |
|
|
Face Detection (SP)
|
100% |
30934
367.6 IPS |
|
|
Face Detection (HP)
|
100% |
44160
524.7 IPS |
|
|
Face Detection (Q)
|
97% |
26763
319.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
58996
454.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
107113
825.2 IPS |
|
|
Depth Estimation (Q)
|
78% |
46224
369.1 IPS |
|
|
Style Transfer (SP)
|
100% |
259101
333.1 IPS |
|
|
Style Transfer (HP)
|
100% |
572212
735.6 IPS |
|
|
Style Transfer (Q)
|
98% |
230752
297.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
43419
1.60 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
51347
1.90 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31719
1.17 KIPS |
|
|
Text Classification (SP)
|
100% |
3015
4.02 KIPS |
|
|
Text Classification (HP)
|
99% |
3534
4.72 KIPS |
|
|
Text Classification (Q)
|
97% |
1976
2.65 KIPS |
|
|
Machine Translation (SP)
|
100% |
4651
80.1 IPS |
|
|
Machine Translation (HP)
|
100% |
4681
80.6 IPS |
|
|
Machine Translation (Q)
|
70% |
2158
40.5 IPS |
