vivo V2324HA
Geekbench ML Score
1260
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 25 2024 08:10 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
806
150.8 IPS |
|
|
Image Classification (F16)
|
100% |
775
145.0 IPS |
|
|
Image Classification (I8)
|
97% |
1454
272.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1061
17.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
980
16.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1056
17.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1433
1.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
1280
1.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
4868
5.89 IPS |
|
|
Object Detection (F32)
|
100% |
620
46.3 IPS |
|
|
Object Detection (F16)
|
100% |
649
48.5 IPS |
|
|
Object Detection (I8)
|
61% |
925
69.0 IPS |
|
|
Face Detection (F32)
|
100% |
1511
18.0 IPS |
|
|
Face Detection (F16)
|
100% |
1594
19.0 IPS |
|
|
Face Detection (I8)
|
86% |
1893
22.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1413
11.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
1406
10.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
1998
15.5 IPS |
|
|
Style Transfer (F32)
|
100% |
2137
2.81 IPS |
|
|
Style Transfer (F16)
|
100% |
2071
2.72 IPS |
|
|
Style Transfer (I8)
|
98% |
3980
5.24 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
892
31.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
876
31.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2059
73.5 IPS |
|
|
Text Classification (F32)
|
100% |
840
1.21 KIPS |
|
|
Text Classification (F16)
|
100% |
839
1.21 KIPS |
|
|
Text Classification (I8)
|
92% |
684
982.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1492
27.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1461
26.9 IPS |
|
|
Machine Translation (I8)
|
64% |
587
10.8 IPS |
