HONOR PTP-N49
Geekbench AI Score
262
Single Precision Score
243
Half Precision Score
553
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | y561994 |
| Upload Date | November 28 2025 09:13 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
312
58.1 IPS |
|
|
Image Classification (HP)
|
100% |
144
26.9 IPS |
|
|
Image Classification (Q)
|
99% |
359
67.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
178
2.89 IPS |
|
|
Image Segmentation (HP)
|
100% |
177
2.87 IPS |
|
|
Image Segmentation (Q)
|
98% |
373
6.06 IPS |
|
|
Pose Estimation (SP)
|
100% |
248
0.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
248
0.29 IPS |
|
|
Pose Estimation (Q)
|
98% |
942
1.10 IPS |
|
|
Object Detection (SP)
|
100% |
135
10.7 IPS |
|
|
Object Detection (HP)
|
100% |
135
10.7 IPS |
|
|
Object Detection (Q)
|
87% |
394
31.6 IPS |
|
|
Face Detection (SP)
|
100% |
376
4.47 IPS |
|
|
Face Detection (HP)
|
100% |
377
4.48 IPS |
|
|
Face Detection (Q)
|
97% |
816
9.74 IPS |
|
|
Depth Estimation (SP)
|
100% |
321
2.47 IPS |
|
|
Depth Estimation (HP)
|
99% |
321
2.47 IPS |
|
|
Depth Estimation (Q)
|
64% |
756
6.86 IPS |
|
|
Style Transfer (SP)
|
100% |
599
0.77 IPS |
|
|
Style Transfer (HP)
|
100% |
598
0.77 IPS |
|
|
Style Transfer (Q)
|
98% |
1658
2.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
160
5.90 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
160
5.90 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
554
20.5 IPS |
|
|
Text Classification (SP)
|
100% |
202
270.0 IPS |
|
|
Text Classification (HP)
|
100% |
203
270.8 IPS |
|
|
Text Classification (Q)
|
91% |
335
450.6 IPS |
|
|
Machine Translation (SP)
|
100% |
356
6.12 IPS |
|
|
Machine Translation (HP)
|
100% |
360
6.19 IPS |
|
|
Machine Translation (Q)
|
57% |
285
6.96 IPS |
