samsung SM-G715FN
Geekbench AI Score
255
Single Precision Score
254
Half Precision Score
309
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | November 03 2025 07:50 AM |
| Views | 3 |
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% |
117
21.8 IPS |
|
|
Image Classification (Q)
|
100% |
210
39.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
153
2.47 IPS |
|
|
Image Segmentation (HP)
|
100% |
154
2.50 IPS |
|
|
Image Segmentation (Q)
|
98% |
276
4.49 IPS |
|
|
Pose Estimation (SP)
|
100% |
574
0.67 IPS |
|
|
Pose Estimation (HP)
|
100% |
562
0.66 IPS |
|
|
Pose Estimation (Q)
|
84% |
431
0.51 IPS |
|
|
Object Detection (SP)
|
100% |
109
8.62 IPS |
|
|
Object Detection (HP)
|
100% |
110
8.70 IPS |
|
|
Object Detection (Q)
|
83% |
204
16.5 IPS |
|
|
Face Detection (SP)
|
100% |
359
4.27 IPS |
|
|
Face Detection (HP)
|
100% |
360
4.27 IPS |
|
|
Face Detection (Q)
|
95% |
505
6.02 IPS |
|
|
Depth Estimation (SP)
|
100% |
453
3.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
430
3.31 IPS |
|
|
Depth Estimation (Q)
|
64% |
456
4.17 IPS |
|
|
Style Transfer (SP)
|
89% |
959
1.25 IPS |
|
|
Style Transfer (HP)
|
89% |
971
1.26 IPS |
|
|
Style Transfer (Q)
|
98% |
1186
1.53 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
252
9.31 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
258
9.54 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
262
9.71 IPS |
|
|
Text Classification (SP)
|
100% |
128
170.4 IPS |
|
|
Text Classification (HP)
|
100% |
126
168.1 IPS |
|
|
Text Classification (Q)
|
88% |
185
249.3 IPS |
|
|
Machine Translation (SP)
|
100% |
212
3.65 IPS |
|
|
Machine Translation (HP)
|
100% |
208
3.58 IPS |
|
|
Machine Translation (Q)
|
50% |
119
4.24 IPS |
