samsung SM-F966B
Geekbench AI Score
2719
Single Precision Score
2458
Half Precision Score
4193
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | teknoseyir |
| Upload Date | August 02 2025 04:02 PM |
| Views | 6 |
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% |
2274
422.9 IPS |
|
|
Image Classification (HP)
|
100% |
2057
382.6 IPS |
|
|
Image Classification (Q)
|
100% |
4509
838.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2521
40.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2586
41.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
5840
95.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
5504
6.42 IPS |
|
|
Pose Estimation (HP)
|
100% |
4214
4.92 IPS |
|
|
Pose Estimation (Q)
|
84% |
12380
14.7 IPS |
|
|
Object Detection (SP)
|
98% |
1458
116.0 IPS |
|
|
Object Detection (HP)
|
98% |
1377
109.5 IPS |
|
|
Object Detection (Q)
|
83% |
3143
253.9 IPS |
|
|
Face Detection (SP)
|
100% |
4106
48.8 IPS |
|
|
Face Detection (HP)
|
100% |
4333
51.5 IPS |
|
|
Face Detection (Q)
|
95% |
8906
106.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
4617
35.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
3815
29.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
7155
65.5 IPS |
|
|
Style Transfer (SP)
|
89% |
10609
13.8 IPS |
|
|
Style Transfer (HP)
|
89% |
9548
12.4 IPS |
|
|
Style Transfer (Q)
|
98% |
18118
23.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1910
70.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2053
75.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5221
193.5 IPS |
|
|
Text Classification (SP)
|
100% |
911
1.22 KIPS |
|
|
Text Classification (HP)
|
99% |
754
1.01 KIPS |
|
|
Text Classification (Q)
|
88% |
588
793.3 IPS |
|
|
Machine Translation (SP)
|
100% |
1373
23.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1068
18.4 IPS |
|
|
Machine Translation (Q)
|
50% |
463
16.4 IPS |
