samsung SM-G715U1
Geekbench AI Score
282
Single Precision Score
280
Half Precision Score
340
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | xRoach |
| Upload Date | January 11 2025 10:24 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | samsung SM-G715U1 |
| Model ID | samsung SM-G715U1 |
| 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% |
133
24.7 IPS |
|
|
Image Classification (HP)
|
100% |
131
24.3 IPS |
|
|
Image Classification (Q)
|
100% |
231
42.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
167
2.70 IPS |
|
|
Image Segmentation (HP)
|
100% |
168
2.72 IPS |
|
|
Image Segmentation (Q)
|
98% |
302
4.91 IPS |
|
|
Pose Estimation (SP)
|
100% |
642
0.75 IPS |
|
|
Pose Estimation (HP)
|
100% |
633
0.74 IPS |
|
|
Pose Estimation (Q)
|
84% |
490
0.58 IPS |
|
|
Object Detection (SP)
|
100% |
120
9.55 IPS |
|
|
Object Detection (HP)
|
100% |
119
9.43 IPS |
|
|
Object Detection (Q)
|
83% |
221
17.8 IPS |
|
|
Face Detection (SP)
|
100% |
394
4.69 IPS |
|
|
Face Detection (HP)
|
100% |
386
4.59 IPS |
|
|
Face Detection (Q)
|
95% |
545
6.50 IPS |
|
|
Depth Estimation (SP)
|
100% |
512
3.94 IPS |
|
|
Depth Estimation (HP)
|
99% |
496
3.82 IPS |
|
|
Depth Estimation (Q)
|
64% |
513
4.70 IPS |
|
|
Style Transfer (SP)
|
89% |
1058
1.37 IPS |
|
|
Style Transfer (HP)
|
89% |
1059
1.37 IPS |
|
|
Style Transfer (Q)
|
98% |
1374
1.77 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
286
10.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
288
10.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
287
10.6 IPS |
|
|
Text Classification (SP)
|
100% |
139
186.1 IPS |
|
|
Text Classification (HP)
|
100% |
139
185.6 IPS |
|
|
Text Classification (Q)
|
88% |
201
270.8 IPS |
|
|
Machine Translation (SP)
|
100% |
224
3.86 IPS |
|
|
Machine Translation (HP)
|
100% |
228
3.93 IPS |
|
|
Machine Translation (Q)
|
50% |
126
4.48 IPS |
