samsung SM-S721B
Geekbench AI Score
3576
Single Precision Score
24899
Half Precision Score
46847
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 28 2024 10:18 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S721B |
| Model ID | samsung SM-S721B |
| Motherboard | s5e9945 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.59 GHz |
| Cluster 3 | 2 Cores @ 2.90 GHz |
| Cluster 4 | 1 Core @ 3.11 GHz |
| Memory Information | |
|---|---|
| Size | 7.06 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1617
300.7 IPS |
|
|
Image Classification (HP)
|
100% |
16721
3.11 KIPS |
|
|
Image Classification (Q)
|
100% |
33062
6.15 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3056
49.5 IPS |
|
|
Image Segmentation (HP)
|
97% |
12346
200.9 IPS |
|
|
Image Segmentation (Q)
|
96% |
27386
445.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
14414
16.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
87024
101.5 IPS |
|
|
Pose Estimation (Q)
|
97% |
302858
354.7 IPS |
|
|
Object Detection (SP)
|
100% |
1598
126.7 IPS |
|
|
Object Detection (HP)
|
100% |
14002
1.11 KIPS |
|
|
Object Detection (Q)
|
90% |
23219
1.86 KIPS |
|
|
Face Detection (SP)
|
100% |
5113
60.8 IPS |
|
|
Face Detection (HP)
|
100% |
39909
474.2 IPS |
|
|
Face Detection (Q)
|
97% |
101149
1.21 KIPS |
|
|
Depth Estimation (SP)
|
100% |
5693
43.9 IPS |
|
|
Depth Estimation (HP)
|
79% |
53677
426.3 IPS |
|
|
Depth Estimation (Q)
|
62% |
106380
1.02 KIPS |
|
|
Style Transfer (SP)
|
100% |
29226
37.6 IPS |
|
|
Style Transfer (HP)
|
99% |
169910
219.1 IPS |
|
|
Style Transfer (Q)
|
98% |
268282
346.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4195
154.9 IPS |
|
|
Image Super-Resolution (HP)
|
83% |
22867
861.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
60058
2.23 KIPS |
|
|
Text Classification (SP)
|
100% |
671
895.7 IPS |
|
|
Text Classification (HP)
|
100% |
7230
9.65 KIPS |
|
|
Text Classification (Q)
|
93% |
8416
11.3 KIPS |
|
|
Machine Translation (SP)
|
100% |
1257
21.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6052
104.3 IPS |
|
|
Machine Translation (Q)
|
56% |
5481
140.6 IPS |
