alps k65v1_64_bsp
Geekbench AI Score
34
Single Precision Score
34
Half Precision Score
61
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 05 2024 05:01 AM |
| Views | 29 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | alps k65v1_64_bsp |
| Model ID | alps k65v1_64_bsp |
| Motherboard | k65v1_64_bsp |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores @ 1.60 GHz |
| Cluster 2 | 4 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 3.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
21
3.90 IPS |
|
|
Image Classification (HP)
|
100% |
21
3.92 IPS |
|
|
Image Classification (Q)
|
99% |
38
7.15 IPS |
|
|
Image Segmentation (SP)
|
100% |
28
0.45 IPS |
|
|
Image Segmentation (HP)
|
100% |
28
0.45 IPS |
|
|
Image Segmentation (Q)
|
98% |
46
0.74 IPS |
|
|
Pose Estimation (SP)
|
100% |
34
0.04 IPS |
|
|
Pose Estimation (HP)
|
100% |
33
0.04 IPS |
|
|
Pose Estimation (Q)
|
98% |
81
0.09 IPS |
|
|
Object Detection (SP)
|
100% |
21
1.68 IPS |
|
|
Object Detection (HP)
|
100% |
22
1.72 IPS |
|
|
Object Detection (Q)
|
87% |
40
3.21 IPS |
|
|
Face Detection (SP)
|
100% |
48
0.57 IPS |
|
|
Face Detection (HP)
|
100% |
48
0.57 IPS |
|
|
Face Detection (Q)
|
97% |
98
1.17 IPS |
|
|
Depth Estimation (SP)
|
100% |
44
0.34 IPS |
|
|
Depth Estimation (HP)
|
99% |
43
0.33 IPS |
|
|
Depth Estimation (Q)
|
64% |
78
0.71 IPS |
|
|
Style Transfer (SP)
|
100% |
75
0.10 IPS |
|
|
Style Transfer (HP)
|
100% |
75
0.10 IPS |
|
|
Style Transfer (Q)
|
98% |
179
0.23 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
25
0.92 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
25
0.93 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
50
1.84 IPS |
|
|
Text Classification (SP)
|
100% |
30
39.8 IPS |
|
|
Text Classification (HP)
|
100% |
30
40.6 IPS |
|
|
Text Classification (Q)
|
91% |
47
63.5 IPS |
|
|
Machine Translation (SP)
|
100% |
50
0.87 IPS |
|
|
Machine Translation (HP)
|
100% |
51
0.88 IPS |
|
|
Machine Translation (Q)
|
57% |
42
1.03 IPS |
