samsung SM-F766B
Geekbench AI Score
438
Single Precision Score
427
Half Precision Score
862
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 22 2025 03:55 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
387
71.9 IPS |
|
|
Image Classification (HP)
|
100% |
384
71.4 IPS |
|
|
Image Classification (Q)
|
99% |
892
166.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
415
6.73 IPS |
|
|
Image Segmentation (HP)
|
100% |
387
6.27 IPS |
|
|
Image Segmentation (Q)
|
98% |
620
10.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
383
0.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
381
0.44 IPS |
|
|
Pose Estimation (Q)
|
98% |
1715
2.01 IPS |
|
|
Object Detection (SP)
|
100% |
244
19.4 IPS |
|
|
Object Detection (HP)
|
100% |
243
19.3 IPS |
|
|
Object Detection (Q)
|
87% |
599
48.1 IPS |
|
|
Face Detection (SP)
|
100% |
663
7.88 IPS |
|
|
Face Detection (HP)
|
100% |
666
7.91 IPS |
|
|
Face Detection (Q)
|
97% |
1314
15.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
502
3.87 IPS |
|
|
Depth Estimation (HP)
|
99% |
465
3.58 IPS |
|
|
Depth Estimation (Q)
|
64% |
1095
9.93 IPS |
|
|
Style Transfer (SP)
|
100% |
758
0.97 IPS |
|
|
Style Transfer (HP)
|
100% |
756
0.97 IPS |
|
|
Style Transfer (Q)
|
98% |
1837
2.37 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
295
10.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
280
10.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
954
35.4 IPS |
|
|
Text Classification (SP)
|
100% |
355
473.8 IPS |
|
|
Text Classification (HP)
|
100% |
362
483.5 IPS |
|
|
Text Classification (Q)
|
91% |
486
652.6 IPS |
|
|
Machine Translation (SP)
|
100% |
663
11.4 IPS |
|
|
Machine Translation (HP)
|
100% |
630
10.9 IPS |
|
|
Machine Translation (Q)
|
57% |
326
7.96 IPS |
