samsung SM-S938B
Geekbench AI Score
713
Single Precision Score
27687
Half Precision Score
62661
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | mihun70 |
| Upload Date | February 25 2025 03:32 PM |
| Views | 16 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938B |
| Model ID | samsung SM-S938B |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
438
81.5 IPS |
|
|
Image Classification (HP)
|
100% |
20883
3.88 KIPS |
|
|
Image Classification (Q)
|
97% |
49292
9.20 KIPS |
|
|
Image Segmentation (SP)
|
100% |
548
8.89 IPS |
|
|
Image Segmentation (HP)
|
100% |
13528
219.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
42386
689.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
725
0.85 IPS |
|
|
Pose Estimation (HP)
|
100% |
123226
143.8 IPS |
|
|
Pose Estimation (Q)
|
98% |
480149
562.0 IPS |
|
|
Object Detection (SP)
|
100% |
417
33.1 IPS |
|
|
Object Detection (HP)
|
100% |
19870
1.58 KIPS |
|
|
Object Detection (Q)
|
85% |
23055
1.86 KIPS |
|
|
Face Detection (SP)
|
100% |
1030
12.2 IPS |
|
|
Face Detection (HP)
|
100% |
43775
520.1 IPS |
|
|
Face Detection (Q)
|
97% |
160111
1.91 KIPS |
|
|
Depth Estimation (SP)
|
100% |
905
6.97 IPS |
|
|
Depth Estimation (HP)
|
99% |
84601
651.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
146395
1.36 KIPS |
|
|
Style Transfer (SP)
|
100% |
1550
1.99 IPS |
|
|
Style Transfer (HP)
|
98% |
99072
127.8 IPS |
|
|
Style Transfer (Q)
|
98% |
494720
637.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
491
18.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
54979
2.03 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134831
5.00 KIPS |
|
|
Text Classification (SP)
|
100% |
646
862.5 IPS |
|
|
Text Classification (HP)
|
100% |
3932
5.25 KIPS |
|
|
Text Classification (Q)
|
93% |
8018
10.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
1029
17.7 IPS |
|
|
Machine Translation (HP)
|
100% |
4826
83.1 IPS |
|
|
Machine Translation (Q)
|
56% |
3219
82.9 IPS |
