alps k6989v1_64_pre
Geekbench ML Score
1087
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 05:15 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | alps k6989v1_64_pre |
| Model ID | alps k6989v1_64_pre |
| Motherboard | k6989v1_64_pre |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 10.97 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
664
124.3 IPS |
|
|
Image Classification (F16)
|
100% |
688
128.7 IPS |
|
|
Image Classification (I8)
|
97% |
861
161.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
855
14.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
868
14.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
973
16.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1035
1.25 IPS |
|
|
Pose Estimation (F16)
|
100% |
1029
1.25 IPS |
|
|
Pose Estimation (I8)
|
100% |
4591
5.56 IPS |
|
|
Object Detection (F32)
|
100% |
588
43.9 IPS |
|
|
Object Detection (F16)
|
100% |
591
44.1 IPS |
|
|
Object Detection (I8)
|
61% |
802
59.9 IPS |
|
|
Face Detection (F32)
|
100% |
1472
17.5 IPS |
|
|
Face Detection (F16)
|
100% |
1428
17.0 IPS |
|
|
Face Detection (I8)
|
86% |
2021
24.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1198
9.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
1169
9.07 IPS |
|
|
Depth Estimation (I8)
|
95% |
1803
14.0 IPS |
|
|
Style Transfer (F32)
|
100% |
1821
2.40 IPS |
|
|
Style Transfer (F16)
|
100% |
1709
2.25 IPS |
|
|
Style Transfer (I8)
|
98% |
4312
5.67 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
775
27.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
777
27.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2112
75.4 IPS |
|
|
Text Classification (F32)
|
100% |
682
979.9 IPS |
|
|
Text Classification (F16)
|
100% |
720
1.03 KIPS |
|
|
Text Classification (I8)
|
92% |
517
742.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1291
23.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1263
23.2 IPS |
|
|
Machine Translation (I8)
|
64% |
427
7.86 IPS |
