nubia NX769J
Geekbench ML Score
1249
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 27 2025 12:26 AM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
779
145.8 IPS |
|
|
Image Classification (F16)
|
100% |
958
179.2 IPS |
|
|
Image Classification (I8)
|
99% |
553
103.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
817
13.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1049
17.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1012
16.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1064
1.29 IPS |
|
|
Pose Estimation (F16)
|
100% |
2487
3.01 IPS |
|
|
Pose Estimation (I8)
|
100% |
2486
3.01 IPS |
|
|
Object Detection (F32)
|
100% |
341
25.5 IPS |
|
|
Object Detection (F16)
|
100% |
391
29.2 IPS |
|
|
Object Detection (I8)
|
62% |
450
33.6 IPS |
|
|
Face Detection (F32)
|
100% |
2289
27.2 IPS |
|
|
Face Detection (F16)
|
97% |
3167
37.7 IPS |
|
|
Face Detection (I8)
|
86% |
2813
33.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1827
14.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
3735
29.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
3702
28.7 IPS |
|
|
Style Transfer (F32)
|
100% |
6610
8.70 IPS |
|
|
Style Transfer (F16)
|
100% |
10600
13.9 IPS |
|
|
Style Transfer (I8)
|
98% |
10600
13.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
573
20.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
991
35.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1079
38.5 IPS |
|
|
Text Classification (F32)
|
100% |
364
523.0 IPS |
|
|
Text Classification (F16)
|
100% |
367
526.7 IPS |
|
|
Text Classification (I8)
|
92% |
604
867.9 IPS |
|
|
Machine Translation (F32)
|
100% |
637
11.7 IPS |
|
|
Machine Translation (F16)
|
100% |
642
11.8 IPS |
|
|
Machine Translation (I8)
|
64% |
725
13.3 IPS |
