vivo V2324HA
Geekbench ML Score
3383
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 08:17 AM |
| Views | 1 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1027
192.2 IPS |
|
|
Image Classification (F16)
|
100% |
4523
846.4 IPS |
|
|
Image Classification (I8)
|
97% |
9346
1.75 KIPS |
|
|
Image Segmentation (F32)
|
100% |
646
10.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
4167
69.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1793
29.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
8573
10.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
17833
21.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
67901
82.2 IPS |
|
|
Object Detection (F32)
|
100% |
699
52.2 IPS |
|
|
Object Detection (F16)
|
100% |
2929
218.7 IPS |
|
|
Object Detection (I8)
|
64% |
3288
245.5 IPS |
|
|
Face Detection (F32)
|
100% |
3567
42.4 IPS |
|
|
Face Detection (F16)
|
97% |
12441
147.9 IPS |
|
|
Face Detection (I8)
|
86% |
11548
137.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
930
7.21 IPS |
|
|
Depth Estimation (F16)
|
100% |
13172
102.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
28935
224.4 IPS |
|
|
Style Transfer (F32)
|
100% |
2549
3.35 IPS |
|
|
Style Transfer (F16)
|
100% |
2409
3.17 IPS |
|
|
Style Transfer (I8)
|
31% |
4691
6.17 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2174
77.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10945
390.9 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
31088
1.11 KIPS |
|
|
Text Classification (F32)
|
100% |
128
183.3 IPS |
|
|
Text Classification (F16)
|
100% |
1988
2.86 KIPS |
|
|
Text Classification (I8)
|
76% |
1082
1.55 KIPS |
|
|
Machine Translation (F32)
|
100% |
387
7.12 IPS |
|
|
Machine Translation (F16)
|
100% |
2240
41.2 IPS |
|
|
Machine Translation (I8)
|
76% |
564
10.4 IPS |
