nubia NX769J
Geekbench ML Score
1106
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 08:44 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | nubia NX769J |
| Model ID | nubia NX769J |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.99 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
544
101.8 IPS |
|
|
Image Classification (F16)
|
100% |
545
101.9 IPS |
|
|
Image Classification (I8)
|
97% |
876
163.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
708
11.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
712
11.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
640
10.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
1392
1.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
1374
1.66 IPS |
|
|
Pose Estimation (I8)
|
100% |
5247
6.35 IPS |
|
|
Object Detection (F32)
|
100% |
557
41.6 IPS |
|
|
Object Detection (F16)
|
100% |
558
41.7 IPS |
|
|
Object Detection (I8)
|
61% |
1094
81.7 IPS |
|
|
Face Detection (F32)
|
100% |
1359
16.2 IPS |
|
|
Face Detection (F16)
|
100% |
1329
15.8 IPS |
|
|
Face Detection (I8)
|
86% |
1842
21.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1313
10.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
1311
10.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
2046
15.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2463
3.24 IPS |
|
|
Style Transfer (F16)
|
100% |
2463
3.24 IPS |
|
|
Style Transfer (I8)
|
98% |
5222
6.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
880
31.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
909
32.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1940
69.3 IPS |
|
|
Text Classification (F32)
|
100% |
648
931.6 IPS |
|
|
Text Classification (F16)
|
100% |
645
926.9 IPS |
|
|
Text Classification (I8)
|
92% |
440
632.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1318
24.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1325
24.4 IPS |
|
|
Machine Translation (I8)
|
64% |
392
7.22 IPS |
