samsung SM-G715FN
Geekbench AI Score
60
Single Precision Score
59
Half Precision Score
87
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | October 24 2024 05:43 AM |
| Views | 15 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
44
8.16 IPS |
|
|
Image Classification (HP)
|
100% |
40
7.51 IPS |
|
|
Image Classification (Q)
|
99% |
56
10.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
44
0.72 IPS |
|
|
Image Segmentation (HP)
|
100% |
45
0.73 IPS |
|
|
Image Segmentation (Q)
|
98% |
62
1.00 IPS |
|
|
Pose Estimation (SP)
|
100% |
64
0.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
64
0.07 IPS |
|
|
Pose Estimation (Q)
|
98% |
121
0.14 IPS |
|
|
Object Detection (SP)
|
100% |
34
2.66 IPS |
|
|
Object Detection (HP)
|
100% |
34
2.67 IPS |
|
|
Object Detection (Q)
|
87% |
58
4.65 IPS |
|
|
Face Detection (SP)
|
100% |
87
1.03 IPS |
|
|
Face Detection (HP)
|
100% |
88
1.05 IPS |
|
|
Face Detection (Q)
|
97% |
133
1.59 IPS |
|
|
Depth Estimation (SP)
|
100% |
77
0.59 IPS |
|
|
Depth Estimation (HP)
|
99% |
77
0.60 IPS |
|
|
Depth Estimation (Q)
|
64% |
113
1.03 IPS |
|
|
Style Transfer (SP)
|
100% |
142
0.18 IPS |
|
|
Style Transfer (HP)
|
100% |
143
0.18 IPS |
|
|
Style Transfer (Q)
|
98% |
274
0.35 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
38
1.41 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
39
1.44 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
71
2.62 IPS |
|
|
Text Classification (SP)
|
100% |
48
64.2 IPS |
|
|
Text Classification (HP)
|
100% |
48
64.7 IPS |
|
|
Text Classification (Q)
|
91% |
61
82.6 IPS |
|
|
Machine Translation (SP)
|
100% |
84
1.45 IPS |
|
|
Machine Translation (HP)
|
100% |
84
1.44 IPS |
|
|
Machine Translation (Q)
|
57% |
63
1.55 IPS |
