VMware, Inc. VBSA
Geekbench AI Score
1075
Single Precision Score
1109
Half Precision Score
2751
Quantized Score
Geekbench AI 1.0.0 for Windows AArch64
Result Information
| User | joedec |
| Upload Date | August 18 2024 04:37 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Apple Part 000 r0p0 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | VMware, Inc. VBSA |
| Motherboard | VMware VBSA |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Apple Part 000 r0p0 |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARMv8 (64-bit) Family 8 Model 0 Revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
327
60.8 IPS |
|
|
Image Classification (HP)
|
100% |
441
82.0 IPS |
|
|
Image Classification (Q)
|
99% |
2392
446.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
511
8.29 IPS |
|
|
Image Segmentation (HP)
|
100% |
1517
24.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
1465
23.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
2178
2.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
3239
3.78 IPS |
|
|
Pose Estimation (Q)
|
95% |
8071
9.46 IPS |
|
|
Object Detection (SP)
|
100% |
456
36.1 IPS |
|
|
Object Detection (HP)
|
99% |
534
42.5 IPS |
|
|
Object Detection (Q)
|
88% |
2193
175.8 IPS |
|
|
Face Detection (SP)
|
100% |
1076
12.8 IPS |
|
|
Face Detection (HP)
|
100% |
787
9.35 IPS |
|
|
Face Detection (Q)
|
97% |
2838
33.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1043
8.03 IPS |
|
|
Depth Estimation (HP)
|
98% |
1674
12.9 IPS |
|
|
Depth Estimation (Q)
|
76% |
6018
48.5 IPS |
|
|
Style Transfer (SP)
|
100% |
5188
6.67 IPS |
|
|
Style Transfer (HP)
|
100% |
5113
6.57 IPS |
|
|
Style Transfer (Q)
|
98% |
13837
17.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1140
42.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
874
32.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2372
87.8 IPS |
|
|
Text Classification (SP)
|
100% |
1205
1.61 KIPS |
|
|
Text Classification (HP)
|
100% |
389
519.4 IPS |
|
|
Text Classification (Q)
|
97% |
421
564.3 IPS |
|
|
Machine Translation (SP)
|
100% |
1554
26.8 IPS |
|
|
Machine Translation (HP)
|
99% |
1065
18.4 IPS |
|
|
Machine Translation (Q)
|
60% |
1700
37.9 IPS |
