samsung SM-X610
Geekbench AI Score
745
Single Precision Score
730
Half Precision Score
1526
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | harsidh |
| Upload Date | July 06 2025 09:01 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-X610 |
| Model ID | samsung SM-X610 |
| 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 | 7.54 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
406
75.6 IPS |
|
|
Image Classification (HP)
|
100% |
395
73.4 IPS |
|
|
Image Classification (Q)
|
100% |
1291
240.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
443
7.18 IPS |
|
|
Image Segmentation (HP)
|
100% |
465
7.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
1436
23.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
1610
1.88 IPS |
|
|
Pose Estimation (HP)
|
100% |
1579
1.84 IPS |
|
|
Pose Estimation (Q)
|
84% |
3093
3.67 IPS |
|
|
Object Detection (SP)
|
100% |
353
28.0 IPS |
|
|
Object Detection (HP)
|
100% |
352
28.0 IPS |
|
|
Object Detection (Q)
|
83% |
1018
82.2 IPS |
|
|
Face Detection (SP)
|
100% |
1056
12.6 IPS |
|
|
Face Detection (HP)
|
100% |
1047
12.4 IPS |
|
|
Face Detection (Q)
|
95% |
2568
30.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
1273
9.81 IPS |
|
|
Depth Estimation (HP)
|
99% |
1136
8.75 IPS |
|
|
Depth Estimation (Q)
|
64% |
2644
24.2 IPS |
|
|
Style Transfer (SP)
|
89% |
2766
3.59 IPS |
|
|
Style Transfer (HP)
|
89% |
2711
3.52 IPS |
|
|
Style Transfer (Q)
|
98% |
6464
8.34 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
784
28.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
767
28.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1423
52.7 IPS |
|
|
Text Classification (SP)
|
100% |
337
450.3 IPS |
|
|
Text Classification (HP)
|
100% |
332
442.8 IPS |
|
|
Text Classification (Q)
|
88% |
635
855.8 IPS |
|
|
Machine Translation (SP)
|
100% |
531
9.14 IPS |
|
|
Machine Translation (HP)
|
100% |
513
8.85 IPS |
|
|
Machine Translation (Q)
|
50% |
297
10.5 IPS |
