samsung SM-S942B
Geekbench AI Score
2556
Single Precision Score
3589
Half Precision Score
3305
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | Neeliix1 |
| Upload Date | March 12 2026 02:09 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-S942B |
| Model ID | samsung SM-S942B |
| Motherboard | s5e9965 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3468 revision 0 |
| Base Frequency | 2.76 GHz |
| Cluster 1 | 6 Cores @ 2.76 GHz |
| Cluster 2 | 3 Cores @ 3.26 GHz |
| Cluster 3 | 1 Core @ 3.80 GHz |
| Memory Information | |
|---|---|
| Size | 11.36 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1830
340.3 IPS |
|
|
Image Classification (HP)
|
100% |
1996
371.1 IPS |
|
|
Image Classification (Q)
|
100% |
2531
470.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2101
34.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2533
41.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
2325
37.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
4872
5.68 IPS |
|
|
Pose Estimation (HP)
|
97% |
12216
14.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
9213
10.8 IPS |
|
|
Object Detection (SP)
|
98% |
1743
138.7 IPS |
|
|
Object Detection (HP)
|
99% |
2032
161.7 IPS |
|
|
Object Detection (Q)
|
83% |
2522
203.7 IPS |
|
|
Face Detection (SP)
|
100% |
3969
47.2 IPS |
|
|
Face Detection (HP)
|
100% |
5538
65.8 IPS |
|
|
Face Detection (Q)
|
97% |
4917
58.6 IPS |
|
|
Depth Estimation (SP)
|
98% |
3919
30.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
6827
52.7 IPS |
|
|
Depth Estimation (Q)
|
65% |
6112
55.1 IPS |
|
|
Style Transfer (SP)
|
89% |
7770
10.1 IPS |
|
|
Style Transfer (HP)
|
89% |
12905
16.8 IPS |
|
|
Style Transfer (Q)
|
98% |
13949
18.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2071
76.5 IPS |
|
|
Image Super-Resolution (HP)
|
99% |
3739
138.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4537
168.1 IPS |
|
|
Text Classification (SP)
|
100% |
826
1.10 KIPS |
|
|
Text Classification (HP)
|
100% |
1071
1.43 KIPS |
|
|
Text Classification (Q)
|
87% |
875
1.18 KIPS |
|
|
Machine Translation (SP)
|
100% |
1765
30.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1447
24.9 IPS |
|
|
Machine Translation (Q)
|
52% |
685
20.7 IPS |
