Moorechip Retroid Pocket 4 Pro
Geekbench AI Score
275
Single Precision Score
282
Half Precision Score
653
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | kyhwana2 |
| Upload Date | August 06 2025 07:36 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
148
27.4 IPS |
|
|
Image Classification (HP)
|
100% |
134
24.8 IPS |
|
|
Image Classification (Q)
|
100% |
424
78.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
149
2.42 IPS |
|
|
Image Segmentation (HP)
|
100% |
145
2.36 IPS |
|
|
Image Segmentation (Q)
|
98% |
466
7.57 IPS |
|
|
Pose Estimation (SP)
|
100% |
558
0.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
566
0.66 IPS |
|
|
Pose Estimation (Q)
|
84% |
1174
1.39 IPS |
|
|
Object Detection (SP)
|
100% |
139
11.1 IPS |
|
|
Object Detection (HP)
|
100% |
145
11.5 IPS |
|
|
Object Detection (Q)
|
83% |
477
38.6 IPS |
|
|
Face Detection (SP)
|
100% |
297
3.53 IPS |
|
|
Face Detection (HP)
|
100% |
297
3.53 IPS |
|
|
Face Detection (Q)
|
95% |
821
9.80 IPS |
|
|
Depth Estimation (SP)
|
100% |
297
2.29 IPS |
|
|
Depth Estimation (HP)
|
99% |
425
3.28 IPS |
|
|
Depth Estimation (Q)
|
64% |
1041
9.53 IPS |
|
|
Style Transfer (SP)
|
89% |
1111
1.44 IPS |
|
|
Style Transfer (HP)
|
89% |
1081
1.40 IPS |
|
|
Style Transfer (Q)
|
98% |
2525
3.26 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
248
9.17 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
250
9.24 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
682
25.3 IPS |
|
|
Text Classification (SP)
|
100% |
182
242.9 IPS |
|
|
Text Classification (HP)
|
100% |
184
245.7 IPS |
|
|
Text Classification (Q)
|
88% |
382
515.6 IPS |
|
|
Machine Translation (SP)
|
100% |
335
5.77 IPS |
|
|
Machine Translation (HP)
|
100% |
324
5.58 IPS |
|
|
Machine Translation (Q)
|
50% |
228
8.11 IPS |
