samsung SM-F766U1
Geekbench AI Score
590
Single Precision Score
578
Half Precision Score
1216
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 09 2025 10:02 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F766U1 |
| Model ID | samsung SM-F766U1 |
| Motherboard | s5e9955 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 2 Cores @ 1.80 GHz |
| Cluster 2 | 5 Cores @ 2.36 GHz |
| Cluster 3 | 2 Cores @ 2.75 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 10.95 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
375
69.8 IPS |
|
|
Image Classification (HP)
|
100% |
375
69.7 IPS |
|
|
Image Classification (Q)
|
99% |
911
169.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
471
7.64 IPS |
|
|
Image Segmentation (HP)
|
100% |
487
7.89 IPS |
|
|
Image Segmentation (Q)
|
98% |
943
15.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
594
0.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
543
0.63 IPS |
|
|
Pose Estimation (Q)
|
98% |
2494
2.92 IPS |
|
|
Object Detection (SP)
|
100% |
362
28.7 IPS |
|
|
Object Detection (HP)
|
100% |
337
26.7 IPS |
|
|
Object Detection (Q)
|
87% |
856
68.7 IPS |
|
|
Face Detection (SP)
|
100% |
893
10.6 IPS |
|
|
Face Detection (HP)
|
100% |
884
10.5 IPS |
|
|
Face Detection (Q)
|
97% |
1798
21.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
713
5.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
716
5.52 IPS |
|
|
Depth Estimation (Q)
|
64% |
1494
13.6 IPS |
|
|
Style Transfer (SP)
|
100% |
1082
1.39 IPS |
|
|
Style Transfer (HP)
|
100% |
1071
1.38 IPS |
|
|
Style Transfer (Q)
|
98% |
2806
3.62 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
427
15.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
413
15.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1422
52.7 IPS |
|
|
Text Classification (SP)
|
100% |
525
701.3 IPS |
|
|
Text Classification (HP)
|
100% |
506
675.6 IPS |
|
|
Text Classification (Q)
|
91% |
676
908.6 IPS |
|
|
Machine Translation (SP)
|
100% |
885
15.2 IPS |
|
|
Machine Translation (HP)
|
100% |
885
15.2 IPS |
|
|
Machine Translation (Q)
|
57% |
532
13.0 IPS |
