HONOR DNN-AN00
Geekbench AI Score
1034
Single Precision Score
1724
Half Precision Score
1297
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 16 2025 07:37 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM SM7750 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR DNN-AN00 |
| Model ID | HONOR DNN-AN00 |
| Motherboard | DNN |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM SM7750 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3457 revision 1 |
| Base Frequency | 1.84 GHz |
| Cluster 1 | 3 Cores @ 1.84 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 11.07 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
736
136.9 IPS |
|
|
Image Classification (HP)
|
100% |
1279
237.8 IPS |
|
|
Image Classification (Q)
|
100% |
1037
192.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1191
19.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1893
30.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
1674
27.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
4361
5.09 IPS |
|
|
Pose Estimation (HP)
|
99% |
8194
9.59 IPS |
|
|
Pose Estimation (Q)
|
96% |
7879
9.23 IPS |
|
|
Object Detection (SP)
|
100% |
609
48.3 IPS |
|
|
Object Detection (HP)
|
99% |
1010
80.1 IPS |
|
|
Object Detection (Q)
|
87% |
1026
82.4 IPS |
|
|
Face Detection (SP)
|
100% |
1813
21.5 IPS |
|
|
Face Detection (HP)
|
100% |
3787
45.0 IPS |
|
|
Face Detection (Q)
|
97% |
2776
33.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
2520
19.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
4541
35.1 IPS |
|
|
Depth Estimation (Q)
|
61% |
3463
34.1 IPS |
|
|
Style Transfer (SP)
|
100% |
5118
6.58 IPS |
|
|
Style Transfer (HP)
|
100% |
10237
13.2 IPS |
|
|
Style Transfer (Q)
|
98% |
10237
13.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1013
37.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1729
63.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1595
59.1 IPS |
|
|
Text Classification (SP)
|
35% |
37
364.2 IPS |
|
|
Text Classification (HP)
|
35% |
57
516.7 IPS |
|
|
Text Classification (Q)
|
33% |
42
507.6 IPS |
|
|
Machine Translation (SP)
|
100% |
686
11.8 IPS |
|
|
Machine Translation (HP)
|
97% |
671
11.6 IPS |
|
|
Machine Translation (Q)
|
43% |
146
8.27 IPS |
