OnePlus CPH2491
Geekbench ML Score
724
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 19 2024 04:53 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus CPH2491 |
| Model ID | OnePlus CPH2491 |
| Motherboard | k6983v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.05 GHz |
| Memory Information | |
|---|---|
| Size | 15.08 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
433
81.1 IPS |
|
|
Image Classification (F16)
|
100% |
552
103.3 IPS |
|
|
Image Classification (I8)
|
97% |
585
109.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
719
12.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
888
14.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
847
14.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
608
0.74 IPS |
|
|
Pose Estimation (F16)
|
100% |
872
1.06 IPS |
|
|
Pose Estimation (I8)
|
100% |
866
1.05 IPS |
|
|
Object Detection (F32)
|
100% |
315
23.5 IPS |
|
|
Object Detection (F16)
|
100% |
425
31.7 IPS |
|
|
Object Detection (I8)
|
62% |
409
30.5 IPS |
|
|
Face Detection (F32)
|
100% |
1582
18.8 IPS |
|
|
Face Detection (F16)
|
98% |
1939
23.1 IPS |
|
|
Face Detection (I8)
|
86% |
1774
21.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
941
7.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
1134
8.80 IPS |
|
|
Depth Estimation (I8)
|
95% |
1112
8.62 IPS |
|
|
Style Transfer (F32)
|
100% |
2454
3.23 IPS |
|
|
Style Transfer (F16)
|
100% |
3488
4.59 IPS |
|
|
Style Transfer (I8)
|
98% |
3482
4.58 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
481
17.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
668
23.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
639
22.8 IPS |
|
|
Text Classification (F32)
|
100% |
215
309.1 IPS |
|
|
Text Classification (F16)
|
100% |
218
314.0 IPS |
|
|
Text Classification (I8)
|
92% |
478
686.9 IPS |
|
|
Machine Translation (F32)
|
100% |
331
6.09 IPS |
|
|
Machine Translation (F16)
|
100% |
298
5.48 IPS |
|
|
Machine Translation (I8)
|
64% |
381
7.02 IPS |
