SAMSUNG ELECTRONICS CO., LTD. R560
Geekbench AI Score
89
Single Precision Score
89
Half Precision Score
198
Quantized Score
Geekbench AI 1.2.0 for Windows x86 (64-bit)
Result Information
| User | kot-ubitsa |
| Upload Date | February 08 2025 11:26 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core 2 Duo P8400 |
| System Information | |
|---|---|
| Operating System | Windows 11 Pro (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. R560 |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. R560 |
| CPU Information | |
|---|---|
| Name | Intel Core 2 Duo P8400 |
| Topology | 1 Processor, 2 Cores |
| Identifier | GenuineIntel Family 6 Model 23 Stepping 6 |
| Base Frequency | 2.27 GHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 4.00 GB |
| Type | DDR-2 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
52
9.62 IPS |
|
|
Image Classification (HP)
|
100% |
43
7.99 IPS |
|
|
Image Classification (Q)
|
96% |
153
28.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
53
0.85 IPS |
|
|
Image Segmentation (HP)
|
100% |
57
0.93 IPS |
|
|
Image Segmentation (Q)
|
97% |
126
2.05 IPS |
|
|
Pose Estimation (SP)
|
100% |
89
0.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
137
0.16 IPS |
|
|
Pose Estimation (Q)
|
86% |
301
0.36 IPS |
|
|
Object Detection (SP)
|
100% |
49
3.87 IPS |
|
|
Object Detection (HP)
|
100% |
46
3.66 IPS |
|
|
Object Detection (Q)
|
58% |
108
11.8 IPS |
|
|
Face Detection (SP)
|
100% |
149
1.77 IPS |
|
|
Face Detection (HP)
|
100% |
106
1.26 IPS |
|
|
Face Detection (Q)
|
96% |
298
3.56 IPS |
|
|
Depth Estimation (SP)
|
100% |
126
0.97 IPS |
|
|
Depth Estimation (HP)
|
99% |
132
1.02 IPS |
|
|
Depth Estimation (Q)
|
78% |
320
2.54 IPS |
|
|
Style Transfer (SP)
|
100% |
247
0.32 IPS |
|
|
Style Transfer (HP)
|
100% |
363
0.47 IPS |
|
|
Style Transfer (Q)
|
87% |
566
0.74 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
55
2.02 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
80
2.95 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
167
6.17 IPS |
|
|
Text Classification (SP)
|
100% |
101
134.8 IPS |
|
|
Text Classification (HP)
|
100% |
70
93.4 IPS |
|
|
Text Classification (Q)
|
97% |
86
114.8 IPS |
|
|
Machine Translation (SP)
|
100% |
108
1.85 IPS |
|
|
Machine Translation (HP)
|
100% |
78
1.35 IPS |
|
|
Machine Translation (Q)
|
68% |
194
3.75 IPS |
