OPPO PEEM00
Geekbench AI Score
56
Single Precision Score
56
Half Precision Score
9926
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 09 2024 03:20 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | ARM Qualcomm |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO PEEM00 |
| Model ID | OPPO PEEM00 |
| Motherboard | lahaina |
| Governor | uag |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 7.09 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
32
5.88 IPS |
|
|
Image Classification (HP)
|
100% |
32
5.90 IPS |
|
|
Image Classification (Q)
|
99% |
9006
1.68 KIPS |
|
|
Image Segmentation (SP)
|
100% |
40
0.65 IPS |
|
|
Image Segmentation (HP)
|
100% |
40
0.65 IPS |
|
|
Image Segmentation (Q)
|
98% |
8394
136.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
58
0.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
57
0.07 IPS |
|
|
Pose Estimation (Q)
|
94% |
91133
106.8 IPS |
|
|
Object Detection (SP)
|
100% |
32
2.53 IPS |
|
|
Object Detection (HP)
|
100% |
32
2.56 IPS |
|
|
Object Detection (Q)
|
88% |
4720
378.1 IPS |
|
|
Face Detection (SP)
|
100% |
76
0.90 IPS |
|
|
Face Detection (HP)
|
100% |
77
0.91 IPS |
|
|
Face Detection (Q)
|
97% |
20254
241.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
73
0.56 IPS |
|
|
Depth Estimation (HP)
|
99% |
73
0.57 IPS |
|
|
Depth Estimation (Q)
|
64% |
24883
229.1 IPS |
|
|
Style Transfer (SP)
|
100% |
130
0.17 IPS |
|
|
Style Transfer (HP)
|
100% |
130
0.17 IPS |
|
|
Style Transfer (Q)
|
98% |
96811
124.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39
1.45 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
39
1.45 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
25325
938.4 IPS |
|
|
Text Classification (SP)
|
100% |
55
74.0 IPS |
|
|
Text Classification (HP)
|
100% |
56
74.7 IPS |
|
|
Text Classification (Q)
|
94% |
1910
2.56 KIPS |
|
|
Machine Translation (SP)
|
100% |
85
1.47 IPS |
|
|
Machine Translation (HP)
|
100% |
85
1.47 IPS |
|
|
Machine Translation (Q)
|
37% |
121
12.2 IPS |
