samsung SM-G715FN
Geekbench AI Score
57
Single Precision Score
58
Half Precision Score
87
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | November 03 2025 09:20 AM |
| Views | 3 |
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% |
31
5.85 IPS |
|
|
Image Classification (HP)
|
100% |
33
6.11 IPS |
|
|
Image Classification (Q)
|
99% |
56
10.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
42
0.69 IPS |
|
|
Image Segmentation (HP)
|
100% |
45
0.72 IPS |
|
|
Image Segmentation (Q)
|
98% |
62
1.01 IPS |
|
|
Pose Estimation (SP)
|
100% |
63
0.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
61
0.07 IPS |
|
|
Pose Estimation (Q)
|
98% |
121
0.14 IPS |
|
|
Object Detection (SP)
|
100% |
33
2.62 IPS |
|
|
Object Detection (HP)
|
100% |
33
2.63 IPS |
|
|
Object Detection (Q)
|
87% |
58
4.65 IPS |
|
|
Face Detection (SP)
|
100% |
86
1.02 IPS |
|
|
Face Detection (HP)
|
100% |
87
1.03 IPS |
|
|
Face Detection (Q)
|
97% |
133
1.59 IPS |
|
|
Depth Estimation (SP)
|
100% |
77
0.59 IPS |
|
|
Depth Estimation (HP)
|
99% |
77
0.59 IPS |
|
|
Depth Estimation (Q)
|
64% |
114
1.04 IPS |
|
|
Style Transfer (SP)
|
100% |
142
0.18 IPS |
|
|
Style Transfer (HP)
|
100% |
143
0.18 IPS |
|
|
Style Transfer (Q)
|
98% |
273
0.35 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39
1.43 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
39
1.42 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
71
2.62 IPS |
|
|
Text Classification (SP)
|
100% |
47
62.3 IPS |
|
|
Text Classification (HP)
|
100% |
47
63.2 IPS |
|
|
Text Classification (Q)
|
91% |
61
82.4 IPS |
|
|
Machine Translation (SP)
|
100% |
83
1.43 IPS |
|
|
Machine Translation (HP)
|
100% |
84
1.45 IPS |
|
|
Machine Translation (Q)
|
57% |
63
1.53 IPS |
