vivo V2324HA
Geekbench ML Score
1183
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 03:15 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2324HA |
| Model ID | vivo V2324HA |
| Motherboard | k6989v1_64 |
| 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 @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 14.95 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
689
129.0 IPS |
|
|
Image Classification (F16)
|
100% |
759
142.1 IPS |
|
|
Image Classification (I8)
|
97% |
709
132.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1458
24.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1752
29.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1717
28.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
761
0.92 IPS |
|
|
Pose Estimation (F16)
|
100% |
1163
1.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1160
1.41 IPS |
|
|
Object Detection (F32)
|
100% |
537
40.1 IPS |
|
|
Object Detection (F16)
|
100% |
575
42.9 IPS |
|
|
Object Detection (I8)
|
62% |
641
47.8 IPS |
|
|
Face Detection (F32)
|
100% |
2700
32.1 IPS |
|
|
Face Detection (F16)
|
98% |
3007
35.8 IPS |
|
|
Face Detection (I8)
|
86% |
2166
25.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1679
13.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
2261
17.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
2214
17.2 IPS |
|
|
Style Transfer (F32)
|
100% |
4172
5.49 IPS |
|
|
Style Transfer (F16)
|
100% |
5408
7.11 IPS |
|
|
Style Transfer (I8)
|
98% |
5426
7.14 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
864
30.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1157
41.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1173
41.9 IPS |
|
|
Text Classification (F32)
|
100% |
285
408.9 IPS |
|
|
Text Classification (F16)
|
100% |
285
409.0 IPS |
|
|
Text Classification (I8)
|
92% |
736
1.06 KIPS |
|
|
Machine Translation (F32)
|
100% |
712
13.1 IPS |
|
|
Machine Translation (F16)
|
100% |
692
12.7 IPS |
|
|
Machine Translation (I8)
|
64% |
757
13.9 IPS |
