samsung SM-S901B
Geekbench AI Score
111
Single Precision Score
153
Half Precision Score
149
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | rynoels4 |
| Upload Date | August 27 2024 06:21 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S901B |
| Model ID | samsung SM-S901B |
| Motherboard | exynos7904 |
| Governor | interactive |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3337 revision 2 |
| Base Frequency | 1.69 GHz |
| Cluster 1 | 6 Cores @ 1.69 GHz |
| Cluster 2 | 2 Cores @ 2.08 GHz |
| Memory Information | |
|---|---|
| Size | 3.65 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
86
16.0 IPS |
|
|
Image Classification (HP)
|
100% |
142
26.4 IPS |
|
|
Image Classification (Q)
|
97% |
133
24.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
116
1.88 IPS |
|
|
Image Segmentation (HP)
|
100% |
161
2.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
155
2.53 IPS |
|
|
Pose Estimation (SP)
|
100% |
67
0.08 IPS |
|
|
Pose Estimation (HP)
|
100% |
93
0.11 IPS |
|
|
Pose Estimation (Q)
|
96% |
91
0.11 IPS |
|
|
Object Detection (SP)
|
100% |
74
5.86 IPS |
|
|
Object Detection (HP)
|
100% |
117
9.31 IPS |
|
|
Object Detection (Q)
|
92% |
116
9.24 IPS |
|
|
Face Detection (SP)
|
100% |
279
3.31 IPS |
|
|
Face Detection (HP)
|
100% |
386
4.58 IPS |
|
|
Face Detection (Q)
|
97% |
368
4.39 IPS |
|
|
Depth Estimation (SP)
|
100% |
143
1.10 IPS |
|
|
Depth Estimation (HP)
|
99% |
207
1.59 IPS |
|
|
Depth Estimation (Q)
|
71% |
189
1.58 IPS |
|
|
Style Transfer (SP)
|
100% |
276
0.35 IPS |
|
|
Style Transfer (HP)
|
100% |
439
0.56 IPS |
|
|
Style Transfer (Q)
|
98% |
436
0.56 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
88
3.24 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
135
4.97 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
133
4.94 IPS |
|
|
Text Classification (SP)
|
100% |
58
77.7 IPS |
|
|
Text Classification (HP)
|
100% |
58
77.8 IPS |
|
|
Text Classification (Q)
|
91% |
77
103.9 IPS |
|
|
Machine Translation (SP)
|
100% |
104
1.80 IPS |
|
|
Machine Translation (HP)
|
100% |
105
1.81 IPS |
|
|
Machine Translation (Q)
|
57% |
80
1.95 IPS |
