OPPO PGX110
Geekbench AI Score
551
Single Precision Score
759
Half Precision Score
544
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | 46fy45 |
| Upload Date | October 25 2025 10:39 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO PGX110 |
| Model ID | OPPO PGX110 |
| Motherboard | k6895v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.85 GHz |
| Memory Information | |
|---|---|
| Size | 15.10 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
277
51.5 IPS |
|
|
Image Classification (HP)
|
100% |
248
46.2 IPS |
|
|
Image Classification (Q)
|
97% |
240
44.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
904
14.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1293
21.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
944
15.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
3740
4.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
7929
9.25 IPS |
|
|
Pose Estimation (Q)
|
95% |
7339
8.60 IPS |
|
|
Object Detection (SP)
|
100% |
330
26.2 IPS |
|
|
Object Detection (HP)
|
99% |
360
28.6 IPS |
|
|
Object Detection (Q)
|
83% |
247
19.9 IPS |
|
|
Face Detection (SP)
|
100% |
1351
16.1 IPS |
|
|
Face Detection (HP)
|
100% |
1635
19.4 IPS |
|
|
Face Detection (Q)
|
96% |
1268
15.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1922
14.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
2642
20.4 IPS |
|
|
Depth Estimation (Q)
|
62% |
2012
19.1 IPS |
|
|
Style Transfer (SP)
|
100% |
5176
6.65 IPS |
|
|
Style Transfer (HP)
|
100% |
12033
15.5 IPS |
|
|
Style Transfer (Q)
|
98% |
11376
14.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
581
21.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
660
24.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
782
29.0 IPS |
|
|
Text Classification (SP)
|
35% |
7
67.9 IPS |
|
|
Text Classification (HP)
|
35% |
10
86.5 IPS |
|
|
Text Classification (Q)
|
29% |
5
82.6 IPS |
|
|
Machine Translation (SP)
|
100% |
153
2.64 IPS |
|
|
Machine Translation (HP)
|
100% |
203
3.50 IPS |
|
|
Machine Translation (Q)
|
43% |
49
2.85 IPS |
