samsung SM-F766U1
Geekbench AI Score
590
Single Precision Score
575
Half Precision Score
1204
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 09 2025 09:47 PM |
| Views | 3 |
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% |
387
71.9 IPS |
|
|
Image Classification (HP)
|
100% |
379
70.4 IPS |
|
|
Image Classification (Q)
|
99% |
915
170.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
474
7.69 IPS |
|
|
Image Segmentation (HP)
|
100% |
483
7.82 IPS |
|
|
Image Segmentation (Q)
|
98% |
954
15.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
585
0.68 IPS |
|
|
Pose Estimation (HP)
|
100% |
557
0.65 IPS |
|
|
Pose Estimation (Q)
|
98% |
2479
2.90 IPS |
|
|
Object Detection (SP)
|
100% |
348
27.6 IPS |
|
|
Object Detection (HP)
|
100% |
348
27.6 IPS |
|
|
Object Detection (Q)
|
87% |
788
63.2 IPS |
|
|
Face Detection (SP)
|
100% |
886
10.5 IPS |
|
|
Face Detection (HP)
|
100% |
893
10.6 IPS |
|
|
Face Detection (Q)
|
97% |
1789
21.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
739
5.70 IPS |
|
|
Depth Estimation (HP)
|
99% |
650
5.01 IPS |
|
|
Depth Estimation (Q)
|
64% |
1588
14.4 IPS |
|
|
Style Transfer (SP)
|
100% |
1125
1.45 IPS |
|
|
Style Transfer (HP)
|
100% |
1043
1.34 IPS |
|
|
Style Transfer (Q)
|
98% |
2839
3.66 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
419
15.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
413
15.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1367
50.6 IPS |
|
|
Text Classification (SP)
|
100% |
506
675.0 IPS |
|
|
Text Classification (HP)
|
100% |
506
675.7 IPS |
|
|
Text Classification (Q)
|
91% |
675
907.1 IPS |
|
|
Machine Translation (SP)
|
100% |
881
15.2 IPS |
|
|
Machine Translation (HP)
|
100% |
890
15.3 IPS |
|
|
Machine Translation (Q)
|
57% |
505
12.3 IPS |
