samsung SM-X200
Geekbench AI Score
24
Single Precision Score
364
Half Precision Score
281
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | February 06 2026 10:08 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM UNISOC |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X200 |
| Model ID | samsung SM-X200 |
| Motherboard | ums512_25c10 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM UNISOC |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 8 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 2.42 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
0% |
0
23.5 IPS |
|
|
Image Classification (HP)
|
100% |
218
40.6 IPS |
|
|
Image Classification (Q)
|
97% |
203
37.8 IPS |
|
|
Image Segmentation (SP)
|
73% |
175
3.02 IPS |
|
|
Image Segmentation (HP)
|
100% |
379
6.15 IPS |
|
|
Image Segmentation (Q)
|
98% |
352
5.73 IPS |
|
|
Pose Estimation (SP)
|
100% |
754
0.88 IPS |
|
|
Pose Estimation (HP)
|
100% |
1456
1.70 IPS |
|
|
Pose Estimation (Q)
|
95% |
1435
1.68 IPS |
|
|
Object Detection (SP)
|
1% |
0
9.44 IPS |
|
|
Object Detection (HP)
|
99% |
234
18.6 IPS |
|
|
Object Detection (Q)
|
83% |
218
17.6 IPS |
|
|
Face Detection (SP)
|
0% |
0
5.60 IPS |
|
|
Face Detection (HP)
|
100% |
941
11.2 IPS |
|
|
Face Detection (Q)
|
96% |
797
9.50 IPS |
|
|
Depth Estimation (SP)
|
1% |
1
3.63 IPS |
|
|
Depth Estimation (HP)
|
98% |
899
6.95 IPS |
|
|
Depth Estimation (Q)
|
62% |
705
6.70 IPS |
|
|
Style Transfer (SP)
|
100% |
1052
1.35 IPS |
|
|
Style Transfer (HP)
|
100% |
2158
2.77 IPS |
|
|
Style Transfer (Q)
|
98% |
2138
2.76 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
333
12.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
582
21.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
568
21.0 IPS |
|
|
Text Classification (SP)
|
35% |
8
79.6 IPS |
|
|
Text Classification (HP)
|
35% |
8
70.0 IPS |
|
|
Text Classification (Q)
|
32% |
5
69.1 IPS |
|
|
Machine Translation (SP)
|
100% |
192
3.31 IPS |
|
|
Machine Translation (HP)
|
100% |
175
3.02 IPS |
|
|
Machine Translation (Q)
|
43% |
41
2.40 IPS |
