Getac ZX10G2
Geekbench AI Score
60
Single Precision Score
60
Half Precision Score
152
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | February 25 2025 07:11 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Getac ZX10G2 |
| Model ID | Getac ZX10G2 |
| Motherboard | lahaina |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.71 GHz |
| Memory Information | |
|---|---|
| Size | 7.13 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
34
6.36 IPS |
|
|
Image Classification (HP)
|
100% |
35
6.43 IPS |
|
|
Image Classification (Q)
|
99% |
104
19.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
46
0.74 IPS |
|
|
Image Segmentation (HP)
|
100% |
46
0.75 IPS |
|
|
Image Segmentation (Q)
|
98% |
92
1.49 IPS |
|
|
Pose Estimation (SP)
|
100% |
57
0.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
58
0.07 IPS |
|
|
Pose Estimation (Q)
|
98% |
279
0.33 IPS |
|
|
Object Detection (SP)
|
100% |
35
2.80 IPS |
|
|
Object Detection (HP)
|
100% |
36
2.82 IPS |
|
|
Object Detection (Q)
|
87% |
116
9.32 IPS |
|
|
Face Detection (SP)
|
100% |
82
0.97 IPS |
|
|
Face Detection (HP)
|
100% |
83
0.98 IPS |
|
|
Face Detection (Q)
|
97% |
222
2.65 IPS |
|
|
Depth Estimation (SP)
|
100% |
75
0.58 IPS |
|
|
Depth Estimation (HP)
|
99% |
76
0.59 IPS |
|
|
Depth Estimation (Q)
|
64% |
194
1.76 IPS |
|
|
Style Transfer (SP)
|
100% |
148
0.19 IPS |
|
|
Style Transfer (HP)
|
100% |
147
0.19 IPS |
|
|
Style Transfer (Q)
|
98% |
398
0.51 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
43
1.60 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
43
1.60 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
156
5.76 IPS |
|
|
Text Classification (SP)
|
100% |
54
72.7 IPS |
|
|
Text Classification (HP)
|
100% |
55
73.3 IPS |
|
|
Text Classification (Q)
|
91% |
101
136.3 IPS |
|
|
Machine Translation (SP)
|
100% |
92
1.59 IPS |
|
|
Machine Translation (HP)
|
100% |
92
1.59 IPS |
|
|
Machine Translation (Q)
|
57% |
82
2.02 IPS |
