samsung SM-N975F
Geekbench AI Score
153
Single Precision Score
232
Half Precision Score
160
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| Upload Date | August 23 2024 04:21 PM |
| Views | 6 |
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
15.7 IPS |
|
|
Image Classification (HP)
|
100% |
89
16.6 IPS |
|
|
Image Classification (Q)
|
97% |
184
34.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
180
2.91 IPS |
|
|
Image Segmentation (HP)
|
100% |
219
3.55 IPS |
|
|
Image Segmentation (Q)
|
98% |
91
1.47 IPS |
|
|
Pose Estimation (SP)
|
100% |
583
0.68 IPS |
|
|
Pose Estimation (HP)
|
100% |
2558
2.99 IPS |
|
|
Pose Estimation (Q)
|
98% |
507
0.59 IPS |
|
|
Object Detection (SP)
|
100% |
85
6.76 IPS |
|
|
Object Detection (HP)
|
100% |
86
6.81 IPS |
|
|
Object Detection (Q)
|
89% |
205
16.4 IPS |
|
|
Face Detection (SP)
|
100% |
100
1.19 IPS |
|
|
Face Detection (HP)
|
100% |
224
2.66 IPS |
|
|
Face Detection (Q)
|
97% |
419
4.99 IPS |
|
|
Depth Estimation (SP)
|
100% |
190
1.46 IPS |
|
|
Depth Estimation (HP)
|
100% |
192
1.48 IPS |
|
|
Depth Estimation (Q)
|
73% |
170
1.39 IPS |
|
|
Style Transfer (SP)
|
100% |
235
0.30 IPS |
|
|
Style Transfer (HP)
|
100% |
341
0.44 IPS |
|
|
Style Transfer (Q)
|
98% |
189
0.24 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
293
10.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
661
24.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
97
3.59 IPS |
|
|
Text Classification (SP)
|
100% |
37
49.9 IPS |
|
|
Text Classification (HP)
|
100% |
57
76.1 IPS |
|
|
Text Classification (Q)
|
91% |
31
42.0 IPS |
|
|
Machine Translation (SP)
|
100% |
197
3.39 IPS |
|
|
Machine Translation (HP)
|
100% |
195
3.35 IPS |
|
|
Machine Translation (Q)
|
57% |
161
3.93 IPS |
