alps k6991v1_64
Geekbench ML Score
1443
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 21 2025 08:04 AM |
| Views | 2 |
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% |
813
152.2 IPS |
|
|
Image Classification (F16)
|
100% |
941
176.1 IPS |
|
|
Image Classification (I8)
|
97% |
1046
195.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1256
21.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1243
20.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
1376
23.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1429
1.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
1319
1.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
6154
7.45 IPS |
|
|
Object Detection (F32)
|
100% |
860
64.2 IPS |
|
|
Object Detection (F16)
|
100% |
850
63.5 IPS |
|
|
Object Detection (I8)
|
61% |
1089
81.3 IPS |
|
|
Face Detection (F32)
|
100% |
1952
23.2 IPS |
|
|
Face Detection (F16)
|
100% |
1930
23.0 IPS |
|
|
Face Detection (I8)
|
86% |
3066
36.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1659
12.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
1697
13.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
2680
20.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2399
3.16 IPS |
|
|
Style Transfer (F16)
|
100% |
2367
3.11 IPS |
|
|
Style Transfer (I8)
|
98% |
5677
7.47 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1076
38.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1040
37.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2884
103.0 IPS |
|
|
Text Classification (F32)
|
100% |
913
1.31 KIPS |
|
|
Text Classification (F16)
|
100% |
919
1.32 KIPS |
|
|
Text Classification (I8)
|
92% |
597
858.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1537
28.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1409
25.9 IPS |
|
|
Machine Translation (I8)
|
64% |
386
7.10 IPS |
