ZTE NX724J
Geekbench AI Score
877
Single Precision Score
870
Half Precision Score
2034
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 19 2024 07:19 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | ZTE NX724J |
| Model ID | ZTE NX724J |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3399 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.36 GHz |
| Cluster 3 | 1 Core @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.04 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
484
90.0 IPS |
|
|
Image Classification (HP)
|
100% |
481
89.5 IPS |
|
|
Image Classification (Q)
|
100% |
1362
253.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
563
9.13 IPS |
|
|
Image Segmentation (HP)
|
100% |
555
9.00 IPS |
|
|
Image Segmentation (Q)
|
98% |
2101
34.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2082
2.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
2059
2.40 IPS |
|
|
Pose Estimation (Q)
|
84% |
5030
5.97 IPS |
|
|
Object Detection (SP)
|
100% |
439
34.9 IPS |
|
|
Object Detection (HP)
|
100% |
426
33.8 IPS |
|
|
Object Detection (Q)
|
83% |
1560
126.0 IPS |
|
|
Face Detection (SP)
|
100% |
1094
13.0 IPS |
|
|
Face Detection (HP)
|
100% |
1086
12.9 IPS |
|
|
Face Detection (Q)
|
95% |
3004
35.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
1567
12.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1583
12.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
2673
24.5 IPS |
|
|
Style Transfer (SP)
|
89% |
3122
4.05 IPS |
|
|
Style Transfer (HP)
|
89% |
3152
4.09 IPS |
|
|
Style Transfer (Q)
|
98% |
9048
11.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
812
30.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
808
29.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2201
81.6 IPS |
|
|
Text Classification (SP)
|
100% |
401
534.8 IPS |
|
|
Text Classification (HP)
|
100% |
397
530.2 IPS |
|
|
Text Classification (Q)
|
88% |
788
1.06 KIPS |
|
|
Machine Translation (SP)
|
100% |
622
10.7 IPS |
|
|
Machine Translation (HP)
|
100% |
616
10.6 IPS |
|
|
Machine Translation (Q)
|
50% |
430
15.3 IPS |
