samsung SM-G736U1
Geekbench AI Score
594
Single Precision Score
972
Half Precision Score
888
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | xRoach |
| Upload Date | August 27 2025 06:44 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-G736U1 |
| Model ID | samsung SM-G736U1 |
| Motherboard | lahaina |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.25 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
421
78.3 IPS |
|
|
Image Classification (HP)
|
100% |
661
122.9 IPS |
|
|
Image Classification (Q)
|
99% |
612
114.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
659
10.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1135
18.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
1036
16.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
2257
2.63 IPS |
|
|
Pose Estimation (HP)
|
99% |
4080
4.76 IPS |
|
|
Pose Estimation (Q)
|
97% |
3976
4.66 IPS |
|
|
Object Detection (SP)
|
100% |
385
30.6 IPS |
|
|
Object Detection (HP)
|
99% |
606
48.1 IPS |
|
|
Object Detection (Q)
|
85% |
570
45.9 IPS |
|
|
Face Detection (SP)
|
100% |
1189
14.1 IPS |
|
|
Face Detection (HP)
|
100% |
2162
25.7 IPS |
|
|
Face Detection (Q)
|
97% |
1831
21.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
1412
10.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
2379
18.4 IPS |
|
|
Depth Estimation (Q)
|
65% |
1969
17.7 IPS |
|
|
Style Transfer (SP)
|
100% |
2834
3.64 IPS |
|
|
Style Transfer (HP)
|
100% |
5994
7.71 IPS |
|
|
Style Transfer (Q)
|
98% |
5932
7.65 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
637
23.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1071
39.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1050
38.9 IPS |
|
|
Text Classification (SP)
|
35% |
24
231.0 IPS |
|
|
Text Classification (HP)
|
35% |
34
312.5 IPS |
|
|
Text Classification (Q)
|
35% |
34
307.4 IPS |
|
|
Machine Translation (SP)
|
100% |
312
5.38 IPS |
|
|
Machine Translation (HP)
|
97% |
363
6.27 IPS |
|
|
Machine Translation (Q)
|
64% |
281
5.77 IPS |
