HONOR PTP-N49
Geekbench AI Score
1241
Single Precision Score
1218
Half Precision Score
2006
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | y561994 |
| Upload Date | November 28 2025 05:34 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm SM8750 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR PTP-N49 |
| Model ID | HONOR PTP-N49 |
| Motherboard | PTP |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm SM8750 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 10.94 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1290
239.8 IPS |
|
|
Image Classification (HP)
|
100% |
806
149.9 IPS |
|
|
Image Classification (Q)
|
100% |
1463
272.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
975
15.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
996
16.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1911
31.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2309
2.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
2322
2.71 IPS |
|
|
Pose Estimation (Q)
|
84% |
5482
6.50 IPS |
|
|
Object Detection (SP)
|
98% |
682
54.2 IPS |
|
|
Object Detection (HP)
|
98% |
719
57.2 IPS |
|
|
Object Detection (Q)
|
83% |
1642
132.6 IPS |
|
|
Face Detection (SP)
|
100% |
2151
25.6 IPS |
|
|
Face Detection (HP)
|
100% |
2155
25.6 IPS |
|
|
Face Detection (Q)
|
95% |
3578
42.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
2036
15.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
1989
15.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
4144
38.0 IPS |
|
|
Style Transfer (SP)
|
89% |
4874
6.33 IPS |
|
|
Style Transfer (HP)
|
89% |
4989
6.48 IPS |
|
|
Style Transfer (Q)
|
98% |
10007
12.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
935
34.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1059
39.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2379
88.1 IPS |
|
|
Text Classification (SP)
|
100% |
336
447.9 IPS |
|
|
Text Classification (HP)
|
99% |
374
499.1 IPS |
|
|
Text Classification (Q)
|
88% |
380
513.0 IPS |
|
|
Machine Translation (SP)
|
100% |
654
11.3 IPS |
|
|
Machine Translation (HP)
|
100% |
634
10.9 IPS |
|
|
Machine Translation (Q)
|
50% |
314
11.2 IPS |
