samsung SM-G715FN
Geekbench AI Score
103
Single Precision Score
138
Half Precision Score
131
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | October 25 2024 09:25 AM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
112
20.7 IPS |
|
|
Image Classification (HP)
|
100% |
179
33.4 IPS |
|
|
Image Classification (Q)
|
99% |
172
32.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
115
1.87 IPS |
|
|
Image Segmentation (HP)
|
100% |
157
2.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
153
2.49 IPS |
|
|
Pose Estimation (SP)
|
100% |
81
0.09 IPS |
|
|
Pose Estimation (HP)
|
100% |
109
0.13 IPS |
|
|
Pose Estimation (Q)
|
96% |
107
0.12 IPS |
|
|
Object Detection (SP)
|
100% |
87
6.88 IPS |
|
|
Object Detection (HP)
|
100% |
100
7.94 IPS |
|
|
Object Detection (Q)
|
83% |
97
7.88 IPS |
|
|
Face Detection (SP)
|
100% |
216
2.57 IPS |
|
|
Face Detection (HP)
|
100% |
302
3.59 IPS |
|
|
Face Detection (Q)
|
97% |
282
3.37 IPS |
|
|
Depth Estimation (SP)
|
100% |
108
0.83 IPS |
|
|
Depth Estimation (HP)
|
99% |
162
1.25 IPS |
|
|
Depth Estimation (Q)
|
62% |
131
1.24 IPS |
|
|
Style Transfer (SP)
|
100% |
216
0.28 IPS |
|
|
Style Transfer (HP)
|
100% |
357
0.46 IPS |
|
|
Style Transfer (Q)
|
98% |
354
0.46 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
76
2.80 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
115
4.26 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
115
4.27 IPS |
|
|
Text Classification (SP)
|
100% |
48
63.9 IPS |
|
|
Text Classification (HP)
|
100% |
48
63.9 IPS |
|
|
Text Classification (Q)
|
91% |
61
81.6 IPS |
|
|
Machine Translation (SP)
|
100% |
85
1.46 IPS |
|
|
Machine Translation (HP)
|
100% |
85
1.46 IPS |
|
|
Machine Translation (Q)
|
57% |
63
1.54 IPS |
