samsung SM-F766U1
Geekbench AI Score
1730
Single Precision Score
2737
Half Precision Score
1982
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 09 2025 09:39 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
944
175.5 IPS |
|
|
Image Classification (HP)
|
100% |
1359
252.7 IPS |
|
|
Image Classification (Q)
|
100% |
1350
251.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2113
34.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
3269
53.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2917
47.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
9231
10.8 IPS |
|
|
Pose Estimation (HP)
|
99% |
16215
18.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
15582
18.3 IPS |
|
|
Object Detection (SP)
|
100% |
767
60.8 IPS |
|
|
Object Detection (HP)
|
99% |
1177
93.4 IPS |
|
|
Object Detection (Q)
|
84% |
1059
85.4 IPS |
|
|
Face Detection (SP)
|
100% |
3662
43.5 IPS |
|
|
Face Detection (HP)
|
100% |
5458
64.9 IPS |
|
|
Face Detection (Q)
|
97% |
4979
59.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
4937
38.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
7578
58.6 IPS |
|
|
Depth Estimation (Q)
|
62% |
5990
57.7 IPS |
|
|
Style Transfer (SP)
|
100% |
18207
23.4 IPS |
|
|
Style Transfer (HP)
|
100% |
27601
35.5 IPS |
|
|
Style Transfer (Q)
|
98% |
25781
33.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2794
103.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4330
159.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3798
140.8 IPS |
|
|
Text Classification (SP)
|
29% |
22
375.2 IPS |
|
|
Text Classification (HP)
|
35% |
47
429.9 IPS |
|
|
Text Classification (Q)
|
29% |
23
403.3 IPS |
|
|
Machine Translation (SP)
|
100% |
845
14.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1200
20.7 IPS |
|
|
Machine Translation (Q)
|
42% |
215
13.9 IPS |
