HONOR PTP-N49
Geekbench AI Score
1227
Single Precision Score
1094
Half Precision Score
2052
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | y561994 |
| Upload Date | November 28 2025 05:27 PM |
| Views | 4 |
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% |
833
154.9 IPS |
|
|
Image Classification (HP)
|
100% |
821
152.6 IPS |
|
|
Image Classification (Q)
|
100% |
1678
312.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
971
15.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
964
15.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
2068
33.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
2337
2.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
2319
2.71 IPS |
|
|
Pose Estimation (Q)
|
84% |
5287
6.27 IPS |
|
|
Object Detection (SP)
|
98% |
699
55.6 IPS |
|
|
Object Detection (HP)
|
98% |
694
55.2 IPS |
|
|
Object Detection (Q)
|
83% |
1377
111.3 IPS |
|
|
Face Detection (SP)
|
100% |
2158
25.6 IPS |
|
|
Face Detection (HP)
|
100% |
2037
24.2 IPS |
|
|
Face Detection (Q)
|
95% |
3434
41.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
1999
15.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
1002
7.74 IPS |
|
|
Depth Estimation (Q)
|
64% |
4067
37.3 IPS |
|
|
Style Transfer (SP)
|
89% |
5101
6.62 IPS |
|
|
Style Transfer (HP)
|
89% |
5024
6.52 IPS |
|
|
Style Transfer (Q)
|
98% |
10745
13.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1096
40.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
998
36.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2523
93.5 IPS |
|
|
Text Classification (SP)
|
100% |
392
523.7 IPS |
|
|
Text Classification (HP)
|
99% |
282
376.6 IPS |
|
|
Text Classification (Q)
|
88% |
463
624.4 IPS |
|
|
Machine Translation (SP)
|
100% |
620
10.7 IPS |
|
|
Machine Translation (HP)
|
100% |
669
11.5 IPS |
|
|
Machine Translation (Q)
|
50% |
299
10.6 IPS |
