ZTE Z2469N
Geekbench AI Score
312
Single Precision Score
519
Half Precision Score
440
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| User | andreadandrea |
| Upload Date | December 30 2025 06:00 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | ZTE Z2469N |
| Model ID | ZTE Z2469N |
| Motherboard | ums9632_1h10 |
| Governor | uscfreq |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 2.04 GHz |
| Cluster 1 | 6 Cores @ 2.04 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 3.40 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
178
33.1 IPS |
|
|
Image Classification (HP)
|
100% |
292
54.4 IPS |
|
|
Image Classification (Q)
|
97% |
261
48.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
262
4.25 IPS |
|
|
Image Segmentation (HP)
|
100% |
517
8.38 IPS |
|
|
Image Segmentation (Q)
|
98% |
497
8.08 IPS |
|
|
Pose Estimation (SP)
|
100% |
1093
1.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
2088
2.44 IPS |
|
|
Pose Estimation (Q)
|
95% |
2063
2.42 IPS |
|
|
Object Detection (SP)
|
100% |
163
13.0 IPS |
|
|
Object Detection (HP)
|
99% |
310
24.6 IPS |
|
|
Object Detection (Q)
|
83% |
292
23.6 IPS |
|
|
Face Detection (SP)
|
100% |
636
7.55 IPS |
|
|
Face Detection (HP)
|
100% |
1259
15.0 IPS |
|
|
Face Detection (Q)
|
96% |
1103
13.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
770
5.93 IPS |
|
|
Depth Estimation (HP)
|
98% |
1437
11.1 IPS |
|
|
Depth Estimation (Q)
|
62% |
1128
10.7 IPS |
|
|
Style Transfer (SP)
|
100% |
1825
2.35 IPS |
|
|
Style Transfer (HP)
|
100% |
3864
4.97 IPS |
|
|
Style Transfer (Q)
|
98% |
3787
4.88 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
451
16.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
789
29.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
752
27.9 IPS |
|
|
Text Classification (SP)
|
35% |
10
87.4 IPS |
|
|
Text Classification (HP)
|
29% |
8
133.2 IPS |
|
|
Text Classification (Q)
|
33% |
12
136.9 IPS |
|
|
Machine Translation (SP)
|
100% |
263
4.53 IPS |
|
|
Machine Translation (HP)
|
100% |
330
5.68 IPS |
|
|
Machine Translation (Q)
|
43% |
83
4.84 IPS |
