HONOR JMS-W09
Geekbench AI Score
140
Single Precision Score
216
Half Precision Score
197
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 23 2025 04:44 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR JMS-W09 |
| Model ID | HONOR JMS-W09 |
| Motherboard | HONOR |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 3.57 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
101
18.7 IPS |
|
|
Image Classification (HP)
|
100% |
163
30.4 IPS |
|
|
Image Classification (Q)
|
99% |
153
28.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
145
2.35 IPS |
|
|
Image Segmentation (HP)
|
100% |
232
3.76 IPS |
|
|
Image Segmentation (Q)
|
98% |
219
3.57 IPS |
|
|
Pose Estimation (SP)
|
100% |
489
0.57 IPS |
|
|
Pose Estimation (HP)
|
99% |
814
0.95 IPS |
|
|
Pose Estimation (Q)
|
97% |
800
0.94 IPS |
|
|
Object Detection (SP)
|
100% |
84
6.65 IPS |
|
|
Object Detection (HP)
|
99% |
134
10.6 IPS |
|
|
Object Detection (Q)
|
85% |
127
10.3 IPS |
|
|
Face Detection (SP)
|
100% |
312
3.71 IPS |
|
|
Face Detection (HP)
|
100% |
502
5.96 IPS |
|
|
Face Detection (Q)
|
97% |
449
5.35 IPS |
|
|
Depth Estimation (SP)
|
100% |
305
2.35 IPS |
|
|
Depth Estimation (HP)
|
98% |
468
3.62 IPS |
|
|
Depth Estimation (Q)
|
63% |
385
3.55 IPS |
|
|
Style Transfer (SP)
|
100% |
693
0.89 IPS |
|
|
Style Transfer (HP)
|
100% |
1095
1.41 IPS |
|
|
Style Transfer (Q)
|
98% |
1056
1.36 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
127
4.71 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
190
7.00 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
170
6.31 IPS |
|
|
Text Classification (SP)
|
35% |
6
54.2 IPS |
|
|
Text Classification (HP)
|
35% |
9
82.7 IPS |
|
|
Text Classification (Q)
|
35% |
9
80.6 IPS |
|
|
Machine Translation (SP)
|
100% |
101
1.74 IPS |
|
|
Machine Translation (HP)
|
97% |
127
2.19 IPS |
|
|
Machine Translation (Q)
|
64% |
93
1.90 IPS |
