samsung SM-F766N
Geekbench AI Score
2226
Single Precision Score
2261
Half Precision Score
3606
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 30 2025 02:38 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F766N |
| Model ID | samsung SM-F766N |
| 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% |
2085
387.8 IPS |
|
|
Image Classification (HP)
|
100% |
2252
418.8 IPS |
|
|
Image Classification (Q)
|
100% |
3753
698.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2579
41.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2655
43.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4422
71.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
4127
4.82 IPS |
|
|
Pose Estimation (HP)
|
100% |
3733
4.36 IPS |
|
|
Pose Estimation (Q)
|
84% |
8772
10.4 IPS |
|
|
Object Detection (SP)
|
98% |
1411
112.3 IPS |
|
|
Object Detection (HP)
|
98% |
1458
116.0 IPS |
|
|
Object Detection (Q)
|
83% |
2228
180.0 IPS |
|
|
Face Detection (SP)
|
100% |
3284
39.0 IPS |
|
|
Face Detection (HP)
|
100% |
3217
38.2 IPS |
|
|
Face Detection (Q)
|
95% |
5784
69.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
3351
25.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
3729
28.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
5984
54.8 IPS |
|
|
Style Transfer (SP)
|
89% |
8634
11.2 IPS |
|
|
Style Transfer (HP)
|
89% |
8610
11.2 IPS |
|
|
Style Transfer (Q)
|
98% |
17141
22.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1578
58.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1564
57.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3986
147.7 IPS |
|
|
Text Classification (SP)
|
100% |
617
823.0 IPS |
|
|
Text Classification (HP)
|
99% |
652
869.6 IPS |
|
|
Text Classification (Q)
|
88% |
901
1.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
1034
17.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1021
17.6 IPS |
|
|
Machine Translation (Q)
|
50% |
538
19.1 IPS |
