Panasonic Connect Co., Ltd. CFFV3-1
Geekbench AI Score
1243
Single Precision Score
523
Half Precision Score
2716
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | July 01 2025 11:45 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i5-1245U |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Enterprise (64-bit) |
| Model | Panasonic Connect Co., Ltd. CFFV3-1 |
| Motherboard | Panasonic Connect Co., Ltd. CFFV3-1H |
| CPU Information | |
|---|---|
| Name | Intel Core i5-1245U |
| Topology | 1 Processor, 10 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 154 Stepping 4 |
| Base Frequency | 1.60 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1516
282.0 IPS |
|
|
Image Classification (HP)
|
100% |
312
58.0 IPS |
|
|
Image Classification (Q)
|
99% |
2820
526.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
797
12.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
517
8.38 IPS |
|
|
Image Segmentation (Q)
|
98% |
3910
63.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
2155
2.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
1226
1.43 IPS |
|
|
Pose Estimation (Q)
|
94% |
4032
4.73 IPS |
|
|
Object Detection (SP)
|
100% |
303
24.0 IPS |
|
|
Object Detection (HP)
|
100% |
178
14.1 IPS |
|
|
Object Detection (Q)
|
86% |
2652
213.1 IPS |
|
|
Face Detection (SP)
|
100% |
3529
41.9 IPS |
|
|
Face Detection (HP)
|
100% |
586
6.96 IPS |
|
|
Face Detection (Q)
|
97% |
3738
44.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1665
12.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
540
4.16 IPS |
|
|
Depth Estimation (Q)
|
78% |
4386
35.0 IPS |
|
|
Style Transfer (SP)
|
100% |
4254
5.47 IPS |
|
|
Style Transfer (HP)
|
100% |
2551
3.28 IPS |
|
|
Style Transfer (Q)
|
98% |
6894
8.89 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
449
16.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
368
13.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1592
59.0 IPS |
|
|
Text Classification (SP)
|
100% |
944
1.26 KIPS |
|
|
Text Classification (HP)
|
100% |
403
538.1 IPS |
|
|
Text Classification (Q)
|
97% |
988
1.32 KIPS |
|
|
Machine Translation (SP)
|
100% |
1055
18.2 IPS |
|
|
Machine Translation (HP)
|
100% |
370
6.38 IPS |
|
|
Machine Translation (Q)
|
65% |
1045
21.0 IPS |
