samsung SM-F966W
Geekbench AI Score
464
Single Precision Score
447
Half Precision Score
978
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | SyderAkaris |
| Upload Date | July 26 2025 07:16 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966W |
| Model ID | samsung SM-F966W |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
421
78.3 IPS |
|
|
Image Classification (HP)
|
100% |
392
73.0 IPS |
|
|
Image Classification (Q)
|
99% |
831
155.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
402
6.52 IPS |
|
|
Image Segmentation (HP)
|
100% |
438
7.11 IPS |
|
|
Image Segmentation (Q)
|
98% |
844
13.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
516
0.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
434
0.51 IPS |
|
|
Pose Estimation (Q)
|
98% |
1706
2.00 IPS |
|
|
Object Detection (SP)
|
100% |
242
19.2 IPS |
|
|
Object Detection (HP)
|
100% |
244
19.3 IPS |
|
|
Object Detection (Q)
|
87% |
633
50.8 IPS |
|
|
Face Detection (SP)
|
100% |
643
7.65 IPS |
|
|
Face Detection (HP)
|
100% |
572
6.79 IPS |
|
|
Face Detection (Q)
|
97% |
1233
14.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
493
3.80 IPS |
|
|
Depth Estimation (HP)
|
99% |
492
3.79 IPS |
|
|
Depth Estimation (Q)
|
64% |
1219
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
894
1.15 IPS |
|
|
Style Transfer (HP)
|
100% |
892
1.15 IPS |
|
|
Style Transfer (Q)
|
98% |
2423
3.12 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
282
10.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
282
10.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1088
40.3 IPS |
|
|
Text Classification (SP)
|
100% |
399
532.9 IPS |
|
|
Text Classification (HP)
|
100% |
400
533.6 IPS |
|
|
Text Classification (Q)
|
91% |
615
827.1 IPS |
|
|
Machine Translation (SP)
|
100% |
694
12.0 IPS |
|
|
Machine Translation (HP)
|
100% |
622
10.7 IPS |
|
|
Machine Translation (Q)
|
57% |
434
10.6 IPS |
