Panasonic Corporation CF-54-2
Geekbench AI Score
1017
Single Precision Score
1017
Half Precision Score
1543
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | noderaser |
| Upload Date | December 27 2024 04:25 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i5-6300U CPU @ 2.40GHz |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Panasonic Corporation CF-54-2 |
| Motherboard | Panasonic Corporation CF54-2 |
| Power Plan | Panasonic Power Management |
| CPU Information | |
|---|---|
| Name | Intel Core i5-6300U |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 78 Stepping 3 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 8.02 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
579
107.6 IPS |
|
|
Image Classification (HP)
|
100% |
578
107.5 IPS |
|
|
Image Classification (Q)
|
100% |
923
171.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
632
10.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
632
10.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
1012
16.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1159
1.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
1159
1.35 IPS |
|
|
Pose Estimation (Q)
|
94% |
2144
2.51 IPS |
|
|
Object Detection (SP)
|
100% |
563
44.6 IPS |
|
|
Object Detection (HP)
|
100% |
569
45.1 IPS |
|
|
Object Detection (Q)
|
87% |
960
77.0 IPS |
|
|
Face Detection (SP)
|
100% |
1414
16.8 IPS |
|
|
Face Detection (HP)
|
100% |
1409
16.7 IPS |
|
|
Face Detection (Q)
|
97% |
2411
28.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
1559
12.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
1556
12.0 IPS |
|
|
Depth Estimation (Q)
|
81% |
2507
19.8 IPS |
|
|
Style Transfer (SP)
|
100% |
3452
4.44 IPS |
|
|
Style Transfer (HP)
|
100% |
3432
4.41 IPS |
|
|
Style Transfer (Q)
|
98% |
6076
7.84 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
699
25.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
706
26.1 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
1295
48.0 IPS |
|
|
Text Classification (SP)
|
100% |
819
1.09 KIPS |
|
|
Text Classification (HP)
|
100% |
823
1.10 KIPS |
|
|
Text Classification (Q)
|
91% |
742
997.3 IPS |
|
|
Machine Translation (SP)
|
100% |
1138
19.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1134
19.5 IPS |
|
|
Machine Translation (Q)
|
100% |
1131
19.5 IPS |
