User | for_geekbench |
Upload Date | April 01 2025 02:13 PM |
Views | 9 |
AI Information | |
---|---|
Framework | TensorFlow Lite |
Backend | CPU |
Device | Samsung Exynos 9820 |
System Information | |
---|---|
Operating System | Android 12 |
Model | Samsung Galaxy S10 |
Model ID | samsung SM-G973F |
Motherboard | exynos9820 |
Governor | schedutil |
CPU Information | |
---|---|
Name | ARMv8 |
Topology | 1 Processor, 8 Cores |
Identifier | ARM implementer 83 architecture 8 variant 1 part 3 revision 0 |
Base Frequency | 1.95 GHz |
Cluster 1 | 4 Cores @ 1.95 GHz |
Cluster 2 | 2 Cores @ 2.31 GHz |
Cluster 3 | 2 Cores @ 2.73 GHz |
Memory Information | |
---|---|
Size | 7.25 GB |
Workload | Accuracy | Score | |
---|---|---|---|
Image Classification (SP)
|
100% |
223
41.4 IPS |
|
Image Classification (HP)
|
100% |
221
41.1 IPS |
|
Image Classification (Q)
|
100% |
463
86.1 IPS |
|
Image Segmentation (SP)
|
100% |
252
4.08 IPS |
|
Image Segmentation (HP)
|
100% |
248
4.01 IPS |
|
Image Segmentation (Q)
|
98% |
460
7.47 IPS |
|
Pose Estimation (SP)
|
100% |
960
1.12 IPS |
|
Pose Estimation (HP)
|
100% |
928
1.08 IPS |
|
Pose Estimation (Q)
|
84% |
890
1.06 IPS |
|
Object Detection (SP)
|
100% |
192
15.3 IPS |
|
Object Detection (HP)
|
100% |
193
15.3 IPS |
|
Object Detection (Q)
|
83% |
430
34.7 IPS |
|
Face Detection (SP)
|
100% |
659
7.83 IPS |
|
Face Detection (HP)
|
100% |
658
7.82 IPS |
|
Face Detection (Q)
|
95% |
1203
14.4 IPS |
|
Depth Estimation (SP)
|
100% |
836
6.44 IPS |
|
Depth Estimation (HP)
|
99% |
813
6.27 IPS |
|
Depth Estimation (Q)
|
64% |
957
8.77 IPS |
|
Style Transfer (SP)
|
89% |
1653
2.15 IPS |
|
Style Transfer (HP)
|
89% |
1654
2.15 IPS |
|
Style Transfer (Q)
|
98% |
1792
2.31 IPS |
|
Image Super-Resolution (SP)
|
100% |
369
13.6 IPS |
|
Image Super-Resolution (HP)
|
100% |
379
14.0 IPS |
|
Image Super-Resolution (Q)
|
97% |
419
15.5 IPS |
|
Text Classification (SP)
|
100% |
148
197.6 IPS |
|
Text Classification (HP)
|
100% |
148
197.3 IPS |
|
Text Classification (Q)
|
88% |
233
313.9 IPS |
|
Machine Translation (SP)
|
100% |
269
4.64 IPS |
|
Machine Translation (HP)
|
100% |
283
4.87 IPS |
|
Machine Translation (Q)
|
50% |
162
5.76 IPS |