mPTech Energy_X2_5G
Geekbench AI Score
234
Single Precision Score
319
Half Precision Score
201
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 24 2025 01:07 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | mPTech Energy_X2_5G |
| Model ID | mPTech Energy_X2_5G |
| Motherboard | pri_board |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
134
25.0 IPS |
|
|
Image Classification (HP)
|
100% |
442
82.2 IPS |
|
|
Image Classification (Q)
|
97% |
67
12.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
261
4.24 IPS |
|
|
Image Segmentation (HP)
|
100% |
147
2.38 IPS |
|
|
Image Segmentation (Q)
|
98% |
78
1.27 IPS |
|
|
Pose Estimation (SP)
|
100% |
925
1.08 IPS |
|
|
Pose Estimation (HP)
|
98% |
2155
2.52 IPS |
|
|
Pose Estimation (Q)
|
70% |
1155
1.47 IPS |
|
|
Object Detection (SP)
|
100% |
155
12.3 IPS |
|
|
Object Detection (HP)
|
100% |
105
8.33 IPS |
|
|
Object Detection (Q)
|
80% |
80
6.51 IPS |
|
|
Face Detection (SP)
|
28% |
45
8.46 IPS |
|
|
Face Detection (HP)
|
100% |
269
3.20 IPS |
|
|
Face Detection (Q)
|
97% |
118
1.41 IPS |
|
|
Depth Estimation (SP)
|
100% |
376
2.90 IPS |
|
|
Depth Estimation (HP)
|
99% |
222
1.71 IPS |
|
|
Depth Estimation (Q)
|
57% |
245
2.67 IPS |
|
|
Style Transfer (SP)
|
100% |
732
0.94 IPS |
|
|
Style Transfer (HP)
|
100% |
368
0.47 IPS |
|
|
Style Transfer (Q)
|
98% |
1738
2.24 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
373
13.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
875
32.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
452
16.8 IPS |
|
|
Text Classification (SP)
|
100% |
93
124.5 IPS |
|
|
Text Classification (HP)
|
100% |
166
221.0 IPS |
|
|
Text Classification (Q)
|
93% |
92
123.4 IPS |
|
|
Machine Translation (SP)
|
100% |
230
3.96 IPS |
|
|
Machine Translation (HP)
|
100% |
235
4.05 IPS |
|
|
Machine Translation (Q)
|
55% |
108
2.86 IPS |
