samsung SM-F766U
Geekbench AI Score
423
Single Precision Score
407
Half Precision Score
829
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 10 2025 05:55 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F766U |
| Model ID | samsung SM-F766U |
| 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% |
386
71.8 IPS |
|
|
Image Classification (HP)
|
100% |
380
70.7 IPS |
|
|
Image Classification (Q)
|
99% |
901
168.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
471
7.63 IPS |
|
|
Image Segmentation (HP)
|
100% |
479
7.77 IPS |
|
|
Image Segmentation (Q)
|
98% |
949
15.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
576
0.67 IPS |
|
|
Pose Estimation (HP)
|
100% |
362
0.42 IPS |
|
|
Pose Estimation (Q)
|
98% |
1552
1.82 IPS |
|
|
Object Detection (SP)
|
100% |
240
19.0 IPS |
|
|
Object Detection (HP)
|
100% |
226
17.9 IPS |
|
|
Object Detection (Q)
|
87% |
538
43.2 IPS |
|
|
Face Detection (SP)
|
100% |
567
6.73 IPS |
|
|
Face Detection (HP)
|
100% |
616
7.33 IPS |
|
|
Face Detection (Q)
|
97% |
1140
13.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
437
3.37 IPS |
|
|
Depth Estimation (HP)
|
99% |
448
3.45 IPS |
|
|
Depth Estimation (Q)
|
64% |
974
8.83 IPS |
|
|
Style Transfer (SP)
|
100% |
691
0.89 IPS |
|
|
Style Transfer (HP)
|
100% |
692
0.89 IPS |
|
|
Style Transfer (Q)
|
98% |
1702
2.19 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
255
9.41 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
262
9.66 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
870
32.3 IPS |
|
|
Text Classification (SP)
|
100% |
318
424.0 IPS |
|
|
Text Classification (HP)
|
100% |
323
431.1 IPS |
|
|
Text Classification (Q)
|
91% |
432
580.0 IPS |
|
|
Machine Translation (SP)
|
100% |
534
9.19 IPS |
|
|
Machine Translation (HP)
|
100% |
530
9.14 IPS |
|
|
Machine Translation (Q)
|
57% |
303
7.40 IPS |
