OPPO CPH2201
Geekbench ML Score
507
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 29 2024 08:00 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | OPPO CPH2201 |
| Model ID | OPPO CPH2201 |
| Motherboard | k6889v1_64_k419 |
| CPU Information | |
|---|---|
| Name | ARM MT6889Z/CZA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.60 GHz |
| Memory Information | |
|---|---|
| Size | 7.30 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
241
45.2 IPS |
|
|
Image Classification (F16)
|
100% |
250
46.7 IPS |
|
|
Image Classification (I8)
|
97% |
436
81.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
378
6.31 IPS |
|
|
Image Segmentation (F16)
|
100% |
372
6.21 IPS |
|
|
Image Segmentation (I8)
|
98% |
509
8.50 IPS |
|
|
Pose Estimation (F32)
|
100% |
542
0.66 IPS |
|
|
Pose Estimation (F16)
|
100% |
531
0.64 IPS |
|
|
Pose Estimation (I8)
|
100% |
1945
2.36 IPS |
|
|
Object Detection (F32)
|
100% |
114
8.50 IPS |
|
|
Object Detection (F16)
|
100% |
154
11.5 IPS |
|
|
Object Detection (I8)
|
61% |
586
43.8 IPS |
|
|
Face Detection (F32)
|
100% |
588
6.99 IPS |
|
|
Face Detection (F16)
|
100% |
597
7.10 IPS |
|
|
Face Detection (I8)
|
86% |
896
10.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
567
4.40 IPS |
|
|
Depth Estimation (F16)
|
100% |
593
4.60 IPS |
|
|
Depth Estimation (I8)
|
95% |
1228
9.52 IPS |
|
|
Style Transfer (F32)
|
100% |
1103
1.45 IPS |
|
|
Style Transfer (F16)
|
100% |
1092
1.44 IPS |
|
|
Style Transfer (I8)
|
98% |
2820
3.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
382
13.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
360
12.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1000
35.7 IPS |
|
|
Text Classification (F32)
|
100% |
299
429.0 IPS |
|
|
Text Classification (F16)
|
100% |
279
401.0 IPS |
|
|
Text Classification (I8)
|
92% |
240
344.5 IPS |
|
|
Machine Translation (F32)
|
100% |
554
10.2 IPS |
|
|
Machine Translation (F16)
|
100% |
528
9.72 IPS |
|
|
Machine Translation (I8)
|
64% |
368
6.78 IPS |
