HONOR PTP-N49
Geekbench AI Score
1257
Single Precision Score
1263
Half Precision Score
2038
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | FiyNw |
| Upload Date | August 17 2025 03:58 PM |
| Views | 5 |
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% |
1591
295.9 IPS |
|
|
Image Classification (HP)
|
100% |
1439
267.6 IPS |
|
|
Image Classification (Q)
|
100% |
1337
248.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1029
16.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1059
17.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2294
37.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2404
2.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
2366
2.76 IPS |
|
|
Pose Estimation (Q)
|
84% |
6111
7.25 IPS |
|
|
Object Detection (SP)
|
98% |
788
62.7 IPS |
|
|
Object Detection (HP)
|
98% |
737
58.7 IPS |
|
|
Object Detection (Q)
|
83% |
1740
140.5 IPS |
|
|
Face Detection (SP)
|
100% |
2197
26.1 IPS |
|
|
Face Detection (HP)
|
100% |
2151
25.6 IPS |
|
|
Face Detection (Q)
|
95% |
3922
46.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
1992
15.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
1992
15.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
4333
39.7 IPS |
|
|
Style Transfer (SP)
|
89% |
4753
6.17 IPS |
|
|
Style Transfer (HP)
|
89% |
5013
6.51 IPS |
|
|
Style Transfer (Q)
|
98% |
9537
12.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1060
39.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1022
37.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2208
81.8 IPS |
|
|
Text Classification (SP)
|
100% |
258
344.2 IPS |
|
|
Text Classification (HP)
|
99% |
304
405.2 IPS |
|
|
Text Classification (Q)
|
88% |
377
507.9 IPS |
|
|
Machine Translation (SP)
|
100% |
560
9.64 IPS |
|
|
Machine Translation (HP)
|
100% |
585
10.1 IPS |
|
|
Machine Translation (Q)
|
50% |
282
9.99 IPS |
