samsung SM-F966B
Geekbench AI Score
2465
Single Precision Score
2310
Half Precision Score
3820
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 21 2025 01:24 AM |
| Views | 3 |
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% |
2192
407.7 IPS |
|
|
Image Classification (HP)
|
100% |
1623
301.8 IPS |
|
|
Image Classification (Q)
|
100% |
4174
776.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2351
38.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2437
39.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
5177
84.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
4926
5.75 IPS |
|
|
Pose Estimation (HP)
|
100% |
3886
4.53 IPS |
|
|
Pose Estimation (Q)
|
84% |
9548
11.3 IPS |
|
|
Object Detection (SP)
|
98% |
1167
92.9 IPS |
|
|
Object Detection (HP)
|
98% |
1332
106.0 IPS |
|
|
Object Detection (Q)
|
83% |
3081
248.8 IPS |
|
|
Face Detection (SP)
|
100% |
4283
50.9 IPS |
|
|
Face Detection (HP)
|
100% |
3800
45.2 IPS |
|
|
Face Detection (Q)
|
95% |
7290
87.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
3987
30.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
3616
27.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
7490
68.6 IPS |
|
|
Style Transfer (SP)
|
89% |
8910
11.6 IPS |
|
|
Style Transfer (HP)
|
89% |
8316
10.8 IPS |
|
|
Style Transfer (Q)
|
98% |
16134
20.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1831
67.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1944
71.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5138
190.4 IPS |
|
|
Text Classification (SP)
|
100% |
763
1.02 KIPS |
|
|
Text Classification (HP)
|
99% |
896
1.20 KIPS |
|
|
Text Classification (Q)
|
88% |
556
750.4 IPS |
|
|
Machine Translation (SP)
|
100% |
1320
22.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1066
18.4 IPS |
|
|
Machine Translation (Q)
|
50% |
414
14.7 IPS |
