alps k6989v1_64_pre
Geekbench ML Score
1119
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 05:07 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% |
683
127.7 IPS |
|
|
Image Classification (F16)
|
100% |
722
135.1 IPS |
|
|
Image Classification (I8)
|
97% |
904
169.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
918
15.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
911
15.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
1030
17.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1137
1.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
1056
1.28 IPS |
|
|
Pose Estimation (I8)
|
100% |
4589
5.56 IPS |
|
|
Object Detection (F32)
|
100% |
575
42.9 IPS |
|
|
Object Detection (F16)
|
100% |
584
43.6 IPS |
|
|
Object Detection (I8)
|
61% |
818
61.1 IPS |
|
|
Face Detection (F32)
|
100% |
1492
17.7 IPS |
|
|
Face Detection (F16)
|
100% |
1483
17.6 IPS |
|
|
Face Detection (I8)
|
86% |
1988
23.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1249
9.68 IPS |
|
|
Depth Estimation (F16)
|
100% |
1248
9.68 IPS |
|
|
Depth Estimation (I8)
|
95% |
1849
14.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1888
2.48 IPS |
|
|
Style Transfer (F16)
|
100% |
1862
2.45 IPS |
|
|
Style Transfer (I8)
|
98% |
4274
5.62 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
784
28.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
774
27.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2123
75.8 IPS |
|
|
Text Classification (F32)
|
100% |
745
1.07 KIPS |
|
|
Text Classification (F16)
|
100% |
756
1.09 KIPS |
|
|
Text Classification (I8)
|
92% |
503
723.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1339
24.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1270
23.4 IPS |
|
|
Machine Translation (I8)
|
64% |
431
7.93 IPS |
