samsung SM-F966B
Geekbench AI Score
2133
Single Precision Score
2000
Half Precision Score
3375
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | September 17 2025 02:48 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1605
298.6 IPS |
|
|
Image Classification (HP)
|
100% |
1700
316.1 IPS |
|
|
Image Classification (Q)
|
100% |
3756
698.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2122
34.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2164
35.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
4677
76.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
4912
5.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
3574
4.17 IPS |
|
|
Pose Estimation (Q)
|
84% |
9561
11.3 IPS |
|
|
Object Detection (SP)
|
98% |
1162
92.4 IPS |
|
|
Object Detection (HP)
|
98% |
1302
103.6 IPS |
|
|
Object Detection (Q)
|
83% |
2813
227.2 IPS |
|
|
Face Detection (SP)
|
100% |
3410
40.5 IPS |
|
|
Face Detection (HP)
|
100% |
3702
44.0 IPS |
|
|
Face Detection (Q)
|
95% |
7283
87.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
3746
28.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
2958
22.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
5744
52.6 IPS |
|
|
Style Transfer (SP)
|
89% |
8441
11.0 IPS |
|
|
Style Transfer (HP)
|
89% |
8266
10.7 IPS |
|
|
Style Transfer (Q)
|
98% |
15375
19.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1624
60.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1647
60.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3466
128.4 IPS |
|
|
Text Classification (SP)
|
100% |
500
666.8 IPS |
|
|
Text Classification (HP)
|
99% |
447
597.2 IPS |
|
|
Text Classification (Q)
|
88% |
501
675.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1149
19.8 IPS |
|
|
Machine Translation (HP)
|
100% |
898
15.5 IPS |
|
|
Machine Translation (Q)
|
50% |
364
12.9 IPS |
