samsung SM-N975F
Geekbench AI Score
150
Single Precision Score
235
Half Precision Score
166
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| Upload Date | August 21 2024 06:59 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | samsung SM-N975F |
| Model ID | samsung SM-N975F |
| Motherboard | exynos9825 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 1 part 3 revision 0 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 Cores @ 1.95 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Cluster 3 | 2 Cores @ 2.73 GHz |
| Memory Information | |
|---|---|
| Size | 11.15 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
84
15.6 IPS |
|
|
Image Classification (HP)
|
100% |
87
16.1 IPS |
|
|
Image Classification (Q)
|
97% |
187
34.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
187
3.02 IPS |
|
|
Image Segmentation (HP)
|
100% |
232
3.76 IPS |
|
|
Image Segmentation (Q)
|
98% |
92
1.49 IPS |
|
|
Pose Estimation (SP)
|
100% |
584
0.68 IPS |
|
|
Pose Estimation (HP)
|
100% |
2572
3.00 IPS |
|
|
Pose Estimation (Q)
|
98% |
507
0.59 IPS |
|
|
Object Detection (SP)
|
100% |
85
6.75 IPS |
|
|
Object Detection (HP)
|
100% |
86
6.86 IPS |
|
|
Object Detection (Q)
|
89% |
205
16.4 IPS |
|
|
Face Detection (SP)
|
100% |
107
1.27 IPS |
|
|
Face Detection (HP)
|
100% |
111
1.32 IPS |
|
|
Face Detection (Q)
|
97% |
202
2.41 IPS |
|
|
Depth Estimation (SP)
|
100% |
103
0.80 IPS |
|
|
Depth Estimation (HP)
|
100% |
189
1.46 IPS |
|
|
Depth Estimation (Q)
|
73% |
439
3.59 IPS |
|
|
Style Transfer (SP)
|
100% |
269
0.35 IPS |
|
|
Style Transfer (HP)
|
100% |
337
0.43 IPS |
|
|
Style Transfer (Q)
|
98% |
172
0.22 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
307
11.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
673
24.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
101
3.76 IPS |
|
|
Text Classification (SP)
|
100% |
42
55.4 IPS |
|
|
Text Classification (HP)
|
100% |
125
166.9 IPS |
|
|
Text Classification (Q)
|
91% |
38
50.6 IPS |
|
|
Machine Translation (SP)
|
100% |
197
3.39 IPS |
|
|
Machine Translation (HP)
|
100% |
196
3.37 IPS |
|
|
Machine Translation (Q)
|
57% |
161
3.94 IPS |
