TOSHIBA Satellite C660
Geekbench AI Score
157
Single Precision Score
119
Half Precision Score
170
Quantized Score
Geekbench AI 1.2.0 for Windows x86 (64-bit)
Result Information
| Upload Date | February 19 2025 10:15 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Pentium P6100 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Professionnel (64-bit) |
| Model | TOSHIBA Satellite C660 |
| Motherboard | TOSHIBA PWWAA |
| Power Plan | Atlas Power Scheme |
| CPU Information | |
|---|---|
| Name | Intel Pentium P6100 |
| Topology | 1 Processor, 2 Cores |
| Identifier | GenuineIntel Family 6 Model 37 Stepping 5 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 6.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
98
18.3 IPS |
|
|
Image Classification (HP)
|
100% |
59
10.9 IPS |
|
|
Image Classification (Q)
|
99% |
108
20.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
91
1.48 IPS |
|
|
Image Segmentation (HP)
|
100% |
79
1.28 IPS |
|
|
Image Segmentation (Q)
|
98% |
120
1.96 IPS |
|
|
Pose Estimation (SP)
|
100% |
178
0.21 IPS |
|
|
Pose Estimation (HP)
|
100% |
170
0.20 IPS |
|
|
Pose Estimation (Q)
|
94% |
223
0.26 IPS |
|
|
Object Detection (SP)
|
100% |
92
7.30 IPS |
|
|
Object Detection (HP)
|
100% |
65
5.15 IPS |
|
|
Object Detection (Q)
|
86% |
107
8.57 IPS |
|
|
Face Detection (SP)
|
100% |
285
3.38 IPS |
|
|
Face Detection (HP)
|
100% |
165
1.96 IPS |
|
|
Face Detection (Q)
|
97% |
320
3.81 IPS |
|
|
Depth Estimation (SP)
|
100% |
250
1.92 IPS |
|
|
Depth Estimation (HP)
|
99% |
177
1.37 IPS |
|
|
Depth Estimation (Q)
|
78% |
264
2.10 IPS |
|
|
Style Transfer (SP)
|
100% |
436
0.56 IPS |
|
|
Style Transfer (HP)
|
100% |
480
0.62 IPS |
|
|
Style Transfer (Q)
|
98% |
547
0.70 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
97
3.59 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
103
3.79 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
133
4.92 IPS |
|
|
Text Classification (SP)
|
100% |
119
158.7 IPS |
|
|
Text Classification (HP)
|
100% |
81
108.3 IPS |
|
|
Text Classification (Q)
|
97% |
92
123.5 IPS |
|
|
Machine Translation (SP)
|
100% |
182
3.14 IPS |
|
|
Machine Translation (HP)
|
100% |
97
1.66 IPS |
|
|
Machine Translation (Q)
|
65% |
122
2.46 IPS |
