OPPO PHZ110
Geekbench ML Score
1445
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 30 2026 11:08 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | OPPO PHZ110 |
| Model ID | OPPO PHZ110 |
| Motherboard | k6989v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 14.98 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1060
198.3 IPS |
|
|
Image Classification (F16)
|
100% |
1536
287.4 IPS |
|
|
Image Classification (I8)
|
97% |
1459
273.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1541
25.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1841
30.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1810
30.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
766
0.93 IPS |
|
|
Pose Estimation (F16)
|
100% |
1168
1.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1166
1.41 IPS |
|
|
Object Detection (F32)
|
100% |
747
55.8 IPS |
|
|
Object Detection (F16)
|
100% |
953
71.2 IPS |
|
|
Object Detection (I8)
|
62% |
885
66.1 IPS |
|
|
Face Detection (F32)
|
100% |
3895
46.3 IPS |
|
|
Face Detection (F16)
|
98% |
5040
59.9 IPS |
|
|
Face Detection (I8)
|
86% |
4396
52.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1752
13.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
2408
18.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
2372
18.4 IPS |
|
|
Style Transfer (F32)
|
100% |
4187
5.51 IPS |
|
|
Style Transfer (F16)
|
100% |
5478
7.21 IPS |
|
|
Style Transfer (I8)
|
98% |
5442
7.16 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
937
33.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1196
42.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1200
42.9 IPS |
|
|
Text Classification (F32)
|
100% |
446
641.3 IPS |
|
|
Text Classification (F16)
|
100% |
447
642.7 IPS |
|
|
Text Classification (I8)
|
92% |
708
1.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
688
12.7 IPS |
|
|
Machine Translation (F16)
|
100% |
681
12.5 IPS |
|
|
Machine Translation (I8)
|
64% |
816
15.0 IPS |
