OnePlus CPH2585
Geekbench ML Score
750
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 27 2024 06:12 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus CPH2585 |
| Model ID | OnePlus CPH2585 |
| Motherboard | kalama |
| Governor | uag |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 14.83 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
370
69.3 IPS |
|
|
Image Classification (F16)
|
100% |
368
68.9 IPS |
|
|
Image Classification (I8)
|
97% |
598
111.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
488
8.15 IPS |
|
|
Image Segmentation (F16)
|
100% |
497
8.30 IPS |
|
|
Image Segmentation (I8)
|
98% |
502
8.38 IPS |
|
|
Pose Estimation (F32)
|
100% |
1027
1.24 IPS |
|
|
Pose Estimation (F16)
|
100% |
1014
1.23 IPS |
|
|
Pose Estimation (I8)
|
100% |
3539
4.29 IPS |
|
|
Object Detection (F32)
|
100% |
398
29.7 IPS |
|
|
Object Detection (F16)
|
100% |
397
29.6 IPS |
|
|
Object Detection (I8)
|
61% |
749
55.9 IPS |
|
|
Face Detection (F32)
|
100% |
871
10.4 IPS |
|
|
Face Detection (F16)
|
100% |
879
10.5 IPS |
|
|
Face Detection (I8)
|
86% |
1224
14.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
866
6.72 IPS |
|
|
Depth Estimation (F16)
|
100% |
873
6.77 IPS |
|
|
Depth Estimation (I8)
|
95% |
1454
11.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1685
2.22 IPS |
|
|
Style Transfer (F16)
|
100% |
1692
2.23 IPS |
|
|
Style Transfer (I8)
|
98% |
3088
4.06 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
558
19.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
557
19.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1327
47.4 IPS |
|
|
Text Classification (F32)
|
100% |
411
590.3 IPS |
|
|
Text Classification (F16)
|
100% |
405
582.4 IPS |
|
|
Text Classification (I8)
|
92% |
282
405.2 IPS |
|
|
Machine Translation (F32)
|
100% |
862
15.9 IPS |
|
|
Machine Translation (F16)
|
100% |
860
15.8 IPS |
|
|
Machine Translation (I8)
|
64% |
318
5.85 IPS |
