Panasonic Corporation CF-19-8
Geekbench AI Score
9
Single Precision Score
9
Half Precision Score
7
Quantized Score
Geekbench AI 1.2.0 for Linux x86 (64-bit)
Result Information
| Upload Date | December 27 2024 06:27 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel(R) Core(TM) i5-3610ME CPU @ 2.70GHz |
| System Information | |
|---|---|
| Operating System | Fedora Linux 41 (KDE Plasma) |
| Model | Panasonic Corporation CF-19-8 |
| Motherboard | Panasonic Corporation CF19-8 |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) i5-3610ME CPU @ 2.70GHz |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 58 Stepping 9 |
| Base Frequency | 3.30 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 7.64 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6
1.21 IPS |
|
|
Image Classification (HP)
|
100% |
6
1.15 IPS |
|
|
Image Classification (Q)
|
97% |
5
0.85 IPS |
|
|
Image Segmentation (SP)
|
100% |
8
0.13 IPS |
|
|
Image Segmentation (HP)
|
100% |
8
0.13 IPS |
|
|
Image Segmentation (Q)
|
98% |
6
0.10 IPS |
|
|
Pose Estimation (SP)
|
100% |
9
0.01 IPS |
|
|
Pose Estimation (HP)
|
100% |
9
0.01 IPS |
|
|
Pose Estimation (Q)
|
96% |
7
0.01 IPS |
|
|
Object Detection (SP)
|
100% |
5
0.42 IPS |
|
|
Object Detection (HP)
|
100% |
5
0.42 IPS |
|
|
Object Detection (Q)
|
87% |
4
0.34 IPS |
|
|
Face Detection (SP)
|
100% |
18
0.21 IPS |
|
|
Face Detection (HP)
|
100% |
18
0.21 IPS |
|
|
Face Detection (Q)
|
97% |
14
0.16 IPS |
|
|
Depth Estimation (SP)
|
100% |
13
0.10 IPS |
|
|
Depth Estimation (HP)
|
99% |
13
0.10 IPS |
|
|
Depth Estimation (Q)
|
64% |
9
0.08 IPS |
|
|
Style Transfer (SP)
|
100% |
27
0.03 IPS |
|
|
Style Transfer (HP)
|
100% |
27
0.03 IPS |
|
|
Style Transfer (Q)
|
98% |
21
0.03 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6
0.21 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6
0.21 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4
0.16 IPS |
|
|
Text Classification (SP)
|
100% |
7
9.99 IPS |
|
|
Text Classification (HP)
|
100% |
7
9.88 IPS |
|
|
Text Classification (Q)
|
91% |
6
7.54 IPS |
|
|
Machine Translation (SP)
|
100% |
14
0.24 IPS |
|
|
Machine Translation (HP)
|
100% |
14
0.24 IPS |
|
|
Machine Translation (Q)
|
58% |
8
0.18 IPS |
