samsung SM-F766U1
Geekbench AI Score
591
Single Precision Score
575
Half Precision Score
1217
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 09 2025 09:55 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% |
382
71.0 IPS |
|
|
Image Classification (HP)
|
100% |
378
70.2 IPS |
|
|
Image Classification (Q)
|
99% |
910
169.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
476
7.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
473
7.67 IPS |
|
|
Image Segmentation (Q)
|
98% |
955
15.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
590
0.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
544
0.63 IPS |
|
|
Pose Estimation (Q)
|
98% |
2396
2.80 IPS |
|
|
Object Detection (SP)
|
100% |
355
28.2 IPS |
|
|
Object Detection (HP)
|
100% |
339
26.9 IPS |
|
|
Object Detection (Q)
|
87% |
778
62.4 IPS |
|
|
Face Detection (SP)
|
100% |
866
10.3 IPS |
|
|
Face Detection (HP)
|
100% |
901
10.7 IPS |
|
|
Face Detection (Q)
|
97% |
1832
21.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
739
5.69 IPS |
|
|
Depth Estimation (HP)
|
99% |
677
5.22 IPS |
|
|
Depth Estimation (Q)
|
64% |
1607
14.6 IPS |
|
|
Style Transfer (SP)
|
100% |
1130
1.45 IPS |
|
|
Style Transfer (HP)
|
100% |
1092
1.40 IPS |
|
|
Style Transfer (Q)
|
98% |
2954
3.81 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
415
15.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
419
15.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1425
52.8 IPS |
|
|
Text Classification (SP)
|
100% |
527
703.2 IPS |
|
|
Text Classification (HP)
|
100% |
487
649.4 IPS |
|
|
Text Classification (Q)
|
91% |
703
945.2 IPS |
|
|
Machine Translation (SP)
|
100% |
872
15.0 IPS |
|
|
Machine Translation (HP)
|
100% |
886
15.3 IPS |
|
|
Machine Translation (Q)
|
57% |
505
12.4 IPS |
