alps k6991v1_64
Geekbench ML Score
1008
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 22 2025 01:36 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | alps k6991v1_64 |
| Model ID | alps k6991v1_64 |
| Motherboard | k6991v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 0 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 4 Cores @ 2.10 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.10 GHz |
| Memory Information | |
|---|---|
| Size | 10.76 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
883
165.1 IPS |
|
|
Image Classification (F16)
|
100% |
921
172.3 IPS |
|
|
Image Classification (I8)
|
97% |
1045
195.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
1221
20.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1235
20.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1368
22.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1382
1.67 IPS |
|
|
Pose Estimation (F16)
|
100% |
1314
1.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
6110
7.40 IPS |
|
|
Object Detection (F32)
|
100% |
859
64.2 IPS |
|
|
Object Detection (F16)
|
100% |
853
63.7 IPS |
|
|
Object Detection (I8)
|
61% |
1130
84.4 IPS |
|
|
Face Detection (F32)
|
100% |
1937
23.0 IPS |
|
|
Face Detection (F16)
|
100% |
1907
22.7 IPS |
|
|
Face Detection (I8)
|
86% |
3011
35.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1658
12.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
1594
12.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
2617
20.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2146
2.82 IPS |
|
|
Style Transfer (F16)
|
100% |
1799
2.37 IPS |
|
|
Style Transfer (I8)
|
98% |
3589
4.72 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
543
19.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
449
16.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1282
45.8 IPS |
|
|
Text Classification (F32)
|
100% |
320
459.5 IPS |
|
|
Text Classification (F16)
|
100% |
158
226.7 IPS |
|
|
Text Classification (I8)
|
92% |
313
450.1 IPS |
|
|
Machine Translation (F32)
|
100% |
292
5.37 IPS |
|
|
Machine Translation (F16)
|
100% |
286
5.27 IPS |
|
|
Machine Translation (I8)
|
64% |
181
3.33 IPS |
