HONOR MEP-AN00
Geekbench AI Score
2577
Single Precision Score
3995
Half Precision Score
3381
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | onion83 |
| Upload Date | December 06 2025 04:41 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm SM8750 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | HONOR MEP-AN00 |
| Model ID | HONOR MEP-AN00 |
| Motherboard | MEP |
| 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 | 14.88 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1743
324.2 IPS |
|
|
Image Classification (HP)
|
100% |
2196
408.4 IPS |
|
|
Image Classification (Q)
|
100% |
2022
376.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2981
48.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
5211
84.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
5265
85.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
12716
14.8 IPS |
|
|
Pose Estimation (HP)
|
99% |
22869
26.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
22425
26.3 IPS |
|
|
Object Detection (SP)
|
100% |
1468
116.5 IPS |
|
|
Object Detection (HP)
|
99% |
1915
151.9 IPS |
|
|
Object Detection (Q)
|
85% |
1865
150.1 IPS |
|
|
Face Detection (SP)
|
100% |
5093
60.5 IPS |
|
|
Face Detection (HP)
|
100% |
8480
100.8 IPS |
|
|
Face Detection (Q)
|
97% |
8271
98.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6602
50.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
9064
70.1 IPS |
|
|
Depth Estimation (Q)
|
61% |
7058
68.8 IPS |
|
|
Style Transfer (SP)
|
100% |
15973
20.5 IPS |
|
|
Style Transfer (HP)
|
100% |
35549
45.7 IPS |
|
|
Style Transfer (Q)
|
98% |
35225
45.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3477
128.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5540
204.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5416
200.7 IPS |
|
|
Text Classification (SP)
|
35% |
72
697.8 IPS |
|
|
Text Classification (HP)
|
35% |
77
698.4 IPS |
|
|
Text Classification (Q)
|
33% |
60
675.2 IPS |
|
|
Machine Translation (SP)
|
100% |
991
17.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1774
30.6 IPS |
|
|
Machine Translation (Q)
|
48% |
657
25.2 IPS |
