Moorechip Retroid Pocket 4 Pro
Geekbench AI Score
774
Single Precision Score
1165
Half Precision Score
838
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | kyhwana2 |
| Upload Date | August 06 2025 07:24 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM MT8797Z/CNZA |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Moorechip Retroid Pocket 4 Pro |
| Model ID | Moorechip Retroid Pocket 4 Pro |
| Motherboard | tb8797p1_64_k419 |
| CPU Information | |
|---|---|
| Name | ARM MT8797Z/CNZA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.60 GHz |
| Memory Information | |
|---|---|
| Size | 7.70 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
360
67.0 IPS |
|
|
Image Classification (HP)
|
100% |
479
89.1 IPS |
|
|
Image Classification (Q)
|
97% |
455
84.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
873
14.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1533
24.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1337
21.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
3865
4.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
7299
8.52 IPS |
|
|
Pose Estimation (Q)
|
95% |
7114
8.34 IPS |
|
|
Object Detection (SP)
|
100% |
346
27.4 IPS |
|
|
Object Detection (HP)
|
99% |
397
31.5 IPS |
|
|
Object Detection (Q)
|
83% |
377
30.4 IPS |
|
|
Face Detection (SP)
|
100% |
1752
20.8 IPS |
|
|
Face Detection (HP)
|
100% |
2517
29.9 IPS |
|
|
Face Detection (Q)
|
96% |
1761
21.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
2404
18.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
4043
31.2 IPS |
|
|
Depth Estimation (Q)
|
62% |
3152
29.9 IPS |
|
|
Style Transfer (SP)
|
100% |
6557
8.43 IPS |
|
|
Style Transfer (HP)
|
100% |
14099
18.1 IPS |
|
|
Style Transfer (Q)
|
98% |
13909
17.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1370
50.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1852
68.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1355
50.2 IPS |
|
|
Text Classification (SP)
|
35% |
18
160.5 IPS |
|
|
Text Classification (HP)
|
35% |
24
214.5 IPS |
|
|
Text Classification (Q)
|
29% |
12
211.7 IPS |
|
|
Machine Translation (SP)
|
100% |
271
4.67 IPS |
|
|
Machine Translation (HP)
|
100% |
340
5.86 IPS |
|
|
Machine Translation (Q)
|
43% |
84
4.88 IPS |
