samsung SM-F958N
Geekbench AI Score
1879
Single Precision Score
2039
Half Precision Score
2796
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 01 2025 02:29 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-F958N |
| Model ID | samsung SM-F958N |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 14.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1973
367.0 IPS |
|
|
Image Classification (HP)
|
100% |
2238
416.2 IPS |
|
|
Image Classification (Q)
|
100% |
2494
463.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2604
42.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2675
43.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
4004
65.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1940
2.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
3133
3.66 IPS |
|
|
Pose Estimation (Q)
|
84% |
5650
6.70 IPS |
|
|
Object Detection (SP)
|
98% |
1207
96.0 IPS |
|
|
Object Detection (HP)
|
98% |
1171
93.2 IPS |
|
|
Object Detection (Q)
|
83% |
1575
127.2 IPS |
|
|
Face Detection (SP)
|
100% |
2757
32.8 IPS |
|
|
Face Detection (HP)
|
100% |
2786
33.1 IPS |
|
|
Face Detection (Q)
|
95% |
4280
51.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
2773
21.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
2797
21.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
4112
37.7 IPS |
|
|
Style Transfer (SP)
|
89% |
5657
7.34 IPS |
|
|
Style Transfer (HP)
|
89% |
6774
8.79 IPS |
|
|
Style Transfer (Q)
|
98% |
10735
13.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1286
47.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1401
51.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3159
117.0 IPS |
|
|
Text Classification (SP)
|
100% |
560
747.3 IPS |
|
|
Text Classification (HP)
|
99% |
635
847.3 IPS |
|
|
Text Classification (Q)
|
88% |
1059
1.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
1465
25.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1206
20.8 IPS |
|
|
Machine Translation (Q)
|
50% |
520
18.4 IPS |
