HONOR PTP-N49
Geekbench AI Score
685
Single Precision Score
27575
Half Precision Score
62154
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | slavatsarev |
| Upload Date | November 12 2025 03:39 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| 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% |
417
77.5 IPS |
|
|
Image Classification (HP)
|
100% |
20860
3.88 KIPS |
|
|
Image Classification (Q)
|
97% |
47035
8.78 KIPS |
|
|
Image Segmentation (SP)
|
100% |
532
8.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
14324
232.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
42802
696.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
694
0.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
120446
140.5 IPS |
|
|
Pose Estimation (Q)
|
98% |
480907
562.9 IPS |
|
|
Object Detection (SP)
|
100% |
393
31.2 IPS |
|
|
Object Detection (HP)
|
100% |
19600
1.55 KIPS |
|
|
Object Detection (Q)
|
85% |
23478
1.89 KIPS |
|
|
Face Detection (SP)
|
100% |
1016
12.1 IPS |
|
|
Face Detection (HP)
|
100% |
43473
516.6 IPS |
|
|
Face Detection (Q)
|
97% |
154495
1.84 KIPS |
|
|
Depth Estimation (SP)
|
100% |
866
6.67 IPS |
|
|
Depth Estimation (HP)
|
99% |
82395
634.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
143337
1.33 KIPS |
|
|
Style Transfer (SP)
|
100% |
1473
1.89 IPS |
|
|
Style Transfer (HP)
|
98% |
99103
127.8 IPS |
|
|
Style Transfer (Q)
|
98% |
497527
641.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
469
17.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
55698
2.06 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
136155
5.05 KIPS |
|
|
Text Classification (SP)
|
100% |
622
829.6 IPS |
|
|
Text Classification (HP)
|
100% |
3968
5.30 KIPS |
|
|
Text Classification (Q)
|
93% |
8230
11.0 KIPS |
|
|
Machine Translation (SP)
|
100% |
1005
17.3 IPS |
|
|
Machine Translation (HP)
|
100% |
4594
79.1 IPS |
|
|
Machine Translation (Q)
|
56% |
3066
79.0 IPS |
