samsung SM-F766W
Geekbench AI Score
414
Single Precision Score
402
Half Precision Score
843
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 09 2025 01:07 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F766W |
| Model ID | samsung SM-F766W |
| 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% |
330
61.3 IPS |
|
|
Image Classification (HP)
|
100% |
332
61.8 IPS |
|
|
Image Classification (Q)
|
99% |
761
141.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
434
7.04 IPS |
|
|
Image Segmentation (HP)
|
100% |
437
7.09 IPS |
|
|
Image Segmentation (Q)
|
98% |
826
13.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
475
0.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
391
0.46 IPS |
|
|
Pose Estimation (Q)
|
98% |
1773
2.08 IPS |
|
|
Object Detection (SP)
|
100% |
251
19.9 IPS |
|
|
Object Detection (HP)
|
100% |
239
18.9 IPS |
|
|
Object Detection (Q)
|
87% |
604
48.5 IPS |
|
|
Face Detection (SP)
|
100% |
603
7.16 IPS |
|
|
Face Detection (HP)
|
100% |
628
7.46 IPS |
|
|
Face Detection (Q)
|
97% |
1295
15.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
504
3.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
474
3.65 IPS |
|
|
Depth Estimation (Q)
|
64% |
1104
10.0 IPS |
|
|
Style Transfer (SP)
|
100% |
636
0.82 IPS |
|
|
Style Transfer (HP)
|
100% |
611
0.79 IPS |
|
|
Style Transfer (Q)
|
98% |
1643
2.12 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
268
9.90 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
239
8.83 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
860
31.9 IPS |
|
|
Text Classification (SP)
|
100% |
308
411.0 IPS |
|
|
Text Classification (HP)
|
100% |
318
424.3 IPS |
|
|
Text Classification (Q)
|
91% |
460
617.7 IPS |
|
|
Machine Translation (SP)
|
100% |
554
9.54 IPS |
|
|
Machine Translation (HP)
|
100% |
598
10.3 IPS |
|
|
Machine Translation (Q)
|
57% |
293
7.16 IPS |
