samsung SM-F966B
Geekbench AI Score
489
Single Precision Score
479
Half Precision Score
985
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | epicgeek |
| Upload Date | November 10 2025 03:01 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966B |
| Model ID | samsung SM-F966B |
| 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% |
431
80.2 IPS |
|
|
Image Classification (HP)
|
100% |
428
79.7 IPS |
|
|
Image Classification (Q)
|
99% |
1083
202.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
551
8.93 IPS |
|
|
Image Segmentation (HP)
|
100% |
535
8.67 IPS |
|
|
Image Segmentation (Q)
|
98% |
878
14.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
550
0.64 IPS |
|
|
Pose Estimation (HP)
|
100% |
510
0.60 IPS |
|
|
Pose Estimation (Q)
|
98% |
1925
2.25 IPS |
|
|
Object Detection (SP)
|
100% |
281
22.3 IPS |
|
|
Object Detection (HP)
|
100% |
275
21.8 IPS |
|
|
Object Detection (Q)
|
87% |
679
54.5 IPS |
|
|
Face Detection (SP)
|
100% |
695
8.26 IPS |
|
|
Face Detection (HP)
|
100% |
696
8.27 IPS |
|
|
Face Detection (Q)
|
97% |
1425
17.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
559
4.31 IPS |
|
|
Depth Estimation (HP)
|
99% |
548
4.22 IPS |
|
|
Depth Estimation (Q)
|
64% |
1227
11.1 IPS |
|
|
Style Transfer (SP)
|
100% |
978
1.26 IPS |
|
|
Style Transfer (HP)
|
100% |
901
1.16 IPS |
|
|
Style Transfer (Q)
|
98% |
2324
3.00 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
289
10.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
289
10.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
885
32.8 IPS |
|
|
Text Classification (SP)
|
100% |
319
426.3 IPS |
|
|
Text Classification (HP)
|
100% |
368
491.7 IPS |
|
|
Text Classification (Q)
|
91% |
566
761.2 IPS |
|
|
Machine Translation (SP)
|
100% |
618
10.6 IPS |
|
|
Machine Translation (HP)
|
100% |
548
9.44 IPS |
|
|
Machine Translation (Q)
|
57% |
343
8.38 IPS |
