samsung SM-X510
Geekbench AI Score
496
Single Precision Score
735
Half Precision Score
572
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | kasid |
| Upload Date | October 26 2025 02:27 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-X510 |
| Model ID | samsung SM-X510 |
| Motherboard | s5e8835 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.57 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
256
47.6 IPS |
|
|
Image Classification (HP)
|
100% |
192
35.6 IPS |
|
|
Image Classification (Q)
|
97% |
182
33.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
591
9.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
1213
19.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
1088
17.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2511
2.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
4898
5.72 IPS |
|
|
Pose Estimation (Q)
|
95% |
4797
5.62 IPS |
|
|
Object Detection (SP)
|
100% |
315
25.0 IPS |
|
|
Object Detection (HP)
|
99% |
491
38.9 IPS |
|
|
Object Detection (Q)
|
83% |
449
36.2 IPS |
|
|
Face Detection (SP)
|
100% |
1247
14.8 IPS |
|
|
Face Detection (HP)
|
100% |
1952
23.2 IPS |
|
|
Face Detection (Q)
|
96% |
1866
22.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1643
12.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
2891
22.3 IPS |
|
|
Depth Estimation (Q)
|
62% |
2262
21.5 IPS |
|
|
Style Transfer (SP)
|
100% |
3969
5.10 IPS |
|
|
Style Transfer (HP)
|
100% |
8879
11.4 IPS |
|
|
Style Transfer (Q)
|
98% |
8759
11.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
736
27.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1064
39.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
857
31.7 IPS |
|
|
Text Classification (SP)
|
35% |
6
55.3 IPS |
|
|
Text Classification (HP)
|
35% |
10
86.5 IPS |
|
|
Text Classification (Q)
|
32% |
7
86.2 IPS |
|
|
Machine Translation (SP)
|
100% |
211
3.64 IPS |
|
|
Machine Translation (HP)
|
100% |
156
2.70 IPS |
|
|
Machine Translation (Q)
|
43% |
40
2.30 IPS |
