samsung SM-G715FN
Geekbench AI Score
256
Single Precision Score
254
Half Precision Score
308
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | October 24 2024 07:41 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | samsung SM-G715FN |
| Model ID | samsung SM-G715FN |
| Motherboard | exynos9611 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3337 revision 2 |
| Base Frequency | 1.74 GHz |
| Cluster 1 | 4 Cores @ 1.74 GHz |
| Cluster 2 | 4 Cores @ 2.31 GHz |
| Memory Information | |
|---|---|
| Size | 3.49 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
116
21.5 IPS |
|
|
Image Classification (HP)
|
100% |
116
21.6 IPS |
|
|
Image Classification (Q)
|
100% |
211
39.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
153
2.48 IPS |
|
|
Image Segmentation (HP)
|
100% |
152
2.46 IPS |
|
|
Image Segmentation (Q)
|
98% |
276
4.49 IPS |
|
|
Pose Estimation (SP)
|
100% |
586
0.68 IPS |
|
|
Pose Estimation (HP)
|
100% |
574
0.67 IPS |
|
|
Pose Estimation (Q)
|
84% |
440
0.52 IPS |
|
|
Object Detection (SP)
|
100% |
110
8.72 IPS |
|
|
Object Detection (HP)
|
100% |
110
8.73 IPS |
|
|
Object Detection (Q)
|
83% |
200
16.2 IPS |
|
|
Face Detection (SP)
|
100% |
358
4.25 IPS |
|
|
Face Detection (HP)
|
100% |
350
4.16 IPS |
|
|
Face Detection (Q)
|
95% |
493
5.89 IPS |
|
|
Depth Estimation (SP)
|
100% |
462
3.56 IPS |
|
|
Depth Estimation (HP)
|
99% |
457
3.52 IPS |
|
|
Depth Estimation (Q)
|
64% |
449
4.11 IPS |
|
|
Style Transfer (SP)
|
89% |
942
1.22 IPS |
|
|
Style Transfer (HP)
|
89% |
950
1.23 IPS |
|
|
Style Transfer (Q)
|
98% |
1206
1.55 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
260
9.60 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
254
9.39 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
271
10.0 IPS |
|
|
Text Classification (SP)
|
100% |
129
171.9 IPS |
|
|
Text Classification (HP)
|
100% |
128
171.1 IPS |
|
|
Text Classification (Q)
|
88% |
181
244.3 IPS |
|
|
Machine Translation (SP)
|
100% |
207
3.57 IPS |
|
|
Machine Translation (HP)
|
100% |
204
3.52 IPS |
|
|
Machine Translation (Q)
|
50% |
115
4.10 IPS |
