Win element M600
Geekbench AI Score
3660
Single Precision Score
1744
Half Precision Score
7047
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | SAI9 |
| Upload Date | April 22 2025 09:10 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 9 7940HS |
| System Information | |
|---|---|
| Operating System | Windows 11 Pro (64-bit) |
| Model | Win element M600 |
| Motherboard | Win element M600 |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 7940HS |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 116 Stepping 1 |
| Base Frequency | 4.00 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2252
418.7 IPS |
|
|
Image Classification (HP)
|
100% |
603
112.1 IPS |
|
|
Image Classification (Q)
|
99% |
6480
1.21 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1089
17.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
895
14.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
3835
62.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7019
8.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
5516
6.44 IPS |
|
|
Pose Estimation (Q)
|
94% |
27055
31.7 IPS |
|
|
Object Detection (SP)
|
100% |
3128
248.1 IPS |
|
|
Object Detection (HP)
|
100% |
833
66.1 IPS |
|
|
Object Detection (Q)
|
86% |
8072
648.7 IPS |
|
|
Face Detection (SP)
|
100% |
5504
65.4 IPS |
|
|
Face Detection (HP)
|
100% |
1722
20.5 IPS |
|
|
Face Detection (Q)
|
97% |
10603
126.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
9231
71.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
2702
20.8 IPS |
|
|
Depth Estimation (Q)
|
78% |
8056
64.3 IPS |
|
|
Style Transfer (SP)
|
100% |
17129
22.0 IPS |
|
|
Style Transfer (HP)
|
100% |
14577
18.7 IPS |
|
|
Style Transfer (Q)
|
98% |
27572
35.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2802
103.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2402
88.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3755
139.0 IPS |
|
|
Text Classification (SP)
|
100% |
1450
1.94 KIPS |
|
|
Text Classification (HP)
|
100% |
806
1.08 KIPS |
|
|
Text Classification (Q)
|
97% |
1947
2.61 KIPS |
|
|
Machine Translation (SP)
|
100% |
2268
39.1 IPS |
|
|
Machine Translation (HP)
|
100% |
800
13.8 IPS |
|
|
Machine Translation (Q)
|
65% |
3235
65.0 IPS |
