samsung SM-G715FN
Geekbench AI Score
246
Single Precision Score
245
Half Precision Score
298
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | October 08 2024 07:39 PM |
| Views | 11 |
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% |
114
21.2 IPS |
|
|
Image Classification (HP)
|
100% |
116
21.5 IPS |
|
|
Image Classification (Q)
|
100% |
210
39.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
154
2.50 IPS |
|
|
Image Segmentation (HP)
|
100% |
153
2.49 IPS |
|
|
Image Segmentation (Q)
|
98% |
277
4.51 IPS |
|
|
Pose Estimation (SP)
|
100% |
539
0.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
523
0.61 IPS |
|
|
Pose Estimation (Q)
|
84% |
413
0.49 IPS |
|
|
Object Detection (SP)
|
100% |
105
8.32 IPS |
|
|
Object Detection (HP)
|
100% |
107
8.47 IPS |
|
|
Object Detection (Q)
|
83% |
196
15.8 IPS |
|
|
Face Detection (SP)
|
100% |
347
4.12 IPS |
|
|
Face Detection (HP)
|
100% |
342
4.06 IPS |
|
|
Face Detection (Q)
|
95% |
486
5.80 IPS |
|
|
Depth Estimation (SP)
|
100% |
431
3.32 IPS |
|
|
Depth Estimation (HP)
|
99% |
420
3.23 IPS |
|
|
Depth Estimation (Q)
|
64% |
424
3.88 IPS |
|
|
Style Transfer (SP)
|
89% |
897
1.16 IPS |
|
|
Style Transfer (HP)
|
89% |
914
1.19 IPS |
|
|
Style Transfer (Q)
|
98% |
1162
1.50 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
253
9.33 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
252
9.31 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
250
9.25 IPS |
|
|
Text Classification (SP)
|
100% |
125
167.1 IPS |
|
|
Text Classification (HP)
|
100% |
124
166.1 IPS |
|
|
Text Classification (Q)
|
88% |
177
238.8 IPS |
|
|
Machine Translation (SP)
|
100% |
194
3.35 IPS |
|
|
Machine Translation (HP)
|
100% |
196
3.38 IPS |
|
|
Machine Translation (Q)
|
50% |
111
3.95 IPS |
