samsung SM-G715U1
Geekbench AI Score
72
Single Precision Score
73
Half Precision Score
116
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 12 2025 12:13 AM |
| Views | 22 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | samsung SM-G715U1 |
| Model ID | samsung SM-G715U1 |
| Motherboard | exynos9611 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3337 revision 2 |
| Base Frequency | 1.74 GHz |
| Cluster 1 | 4 Cores @ 1.74 GHz |
| Cluster 2 | 4 Cores @ 2.31 GHz |
| Memory Information | |
|---|---|
| Size | 3.49 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
43
8.04 IPS |
|
|
Image Classification (HP)
|
100% |
43
8.09 IPS |
|
|
Image Classification (Q)
|
99% |
75
14.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
58
0.93 IPS |
|
|
Image Segmentation (HP)
|
100% |
58
0.94 IPS |
|
|
Image Segmentation (Q)
|
98% |
83
1.35 IPS |
|
|
Pose Estimation (SP)
|
100% |
81
0.09 IPS |
|
|
Pose Estimation (HP)
|
100% |
80
0.09 IPS |
|
|
Pose Estimation (Q)
|
98% |
160
0.19 IPS |
|
|
Object Detection (SP)
|
100% |
43
3.42 IPS |
|
|
Object Detection (HP)
|
100% |
43
3.45 IPS |
|
|
Object Detection (Q)
|
87% |
77
6.19 IPS |
|
|
Face Detection (SP)
|
100% |
112
1.33 IPS |
|
|
Face Detection (HP)
|
100% |
112
1.33 IPS |
|
|
Face Detection (Q)
|
97% |
176
2.10 IPS |
|
|
Depth Estimation (SP)
|
100% |
98
0.75 IPS |
|
|
Depth Estimation (HP)
|
99% |
98
0.76 IPS |
|
|
Depth Estimation (Q)
|
64% |
149
1.35 IPS |
|
|
Style Transfer (SP)
|
100% |
136
0.18 IPS |
|
|
Style Transfer (HP)
|
100% |
142
0.18 IPS |
|
|
Style Transfer (Q)
|
98% |
360
0.46 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
49
1.81 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
49
1.80 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
92
3.42 IPS |
|
|
Text Classification (SP)
|
100% |
61
81.7 IPS |
|
|
Text Classification (HP)
|
100% |
62
83.0 IPS |
|
|
Text Classification (Q)
|
91% |
83
111.4 IPS |
|
|
Machine Translation (SP)
|
100% |
106
1.83 IPS |
|
|
Machine Translation (HP)
|
100% |
106
1.83 IPS |
|
|
Machine Translation (Q)
|
57% |
83
2.03 IPS |
