samsung SM-F766B
Geekbench AI Score
2382
Single Precision Score
2248
Half Precision Score
3643
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 15 2025 12:21 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F766B |
| Model ID | samsung SM-F766B |
| 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% |
2283
424.5 IPS |
|
|
Image Classification (HP)
|
100% |
2313
430.1 IPS |
|
|
Image Classification (Q)
|
100% |
3808
708.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2760
44.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2765
44.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
4467
72.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
5395
6.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
3767
4.40 IPS |
|
|
Pose Estimation (Q)
|
84% |
8459
10.0 IPS |
|
|
Object Detection (SP)
|
98% |
1403
111.7 IPS |
|
|
Object Detection (HP)
|
98% |
1449
115.3 IPS |
|
|
Object Detection (Q)
|
83% |
2400
193.9 IPS |
|
|
Face Detection (SP)
|
100% |
3695
43.9 IPS |
|
|
Face Detection (HP)
|
100% |
3176
37.7 IPS |
|
|
Face Detection (Q)
|
95% |
6225
74.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
3136
24.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3074
23.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
5914
54.2 IPS |
|
|
Style Transfer (SP)
|
89% |
8962
11.6 IPS |
|
|
Style Transfer (HP)
|
89% |
8637
11.2 IPS |
|
|
Style Transfer (Q)
|
98% |
16426
21.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1520
56.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1524
56.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4058
150.3 IPS |
|
|
Text Classification (SP)
|
100% |
691
922.0 IPS |
|
|
Text Classification (HP)
|
99% |
654
873.4 IPS |
|
|
Text Classification (Q)
|
88% |
892
1.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
1132
19.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1126
19.4 IPS |
|
|
Machine Translation (Q)
|
50% |
545
19.3 IPS |
