samsung SM-S938N
Geekbench AI Score
2377
Single Precision Score
2396
Half Precision Score
4218
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | November 12 2025 03:26 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-S938N |
| Model ID | samsung SM-S938N |
| 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 | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2215
411.9 IPS |
|
|
Image Classification (HP)
|
100% |
2178
405.0 IPS |
|
|
Image Classification (Q)
|
100% |
4535
843.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2409
39.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2408
39.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
5035
81.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
5051
5.89 IPS |
|
|
Pose Estimation (HP)
|
100% |
5256
6.13 IPS |
|
|
Pose Estimation (Q)
|
84% |
12097
14.3 IPS |
|
|
Object Detection (SP)
|
98% |
1291
102.8 IPS |
|
|
Object Detection (HP)
|
98% |
1062
84.5 IPS |
|
|
Object Detection (Q)
|
83% |
2263
182.8 IPS |
|
|
Face Detection (SP)
|
100% |
2424
28.8 IPS |
|
|
Face Detection (HP)
|
100% |
3586
42.6 IPS |
|
|
Face Detection (Q)
|
95% |
7189
85.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
4431
34.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
4133
31.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
10872
99.6 IPS |
|
|
Style Transfer (SP)
|
89% |
11181
14.5 IPS |
|
|
Style Transfer (HP)
|
89% |
11396
14.8 IPS |
|
|
Style Transfer (Q)
|
98% |
22724
29.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1682
62.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1548
57.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3851
142.7 IPS |
|
|
Text Classification (SP)
|
100% |
633
844.3 IPS |
|
|
Text Classification (HP)
|
99% |
604
805.8 IPS |
|
|
Text Classification (Q)
|
88% |
772
1.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
1299
22.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1354
23.3 IPS |
|
|
Machine Translation (Q)
|
50% |
541
19.2 IPS |
