Win element M600
Geekbench AI Score
2947
Single Precision Score
1404
Half Precision Score
6454
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | SAI9 |
| Upload Date | April 13 2025 12:16 PM |
| 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% |
2300
427.7 IPS |
|
|
Image Classification (HP)
|
100% |
564
104.9 IPS |
|
|
Image Classification (Q)
|
99% |
6769
1.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
630
10.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
742
12.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
3582
58.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
5002
5.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
3699
4.32 IPS |
|
|
Pose Estimation (Q)
|
94% |
19653
23.0 IPS |
|
|
Object Detection (SP)
|
100% |
2589
205.4 IPS |
|
|
Object Detection (HP)
|
100% |
634
50.3 IPS |
|
|
Object Detection (Q)
|
86% |
7333
589.3 IPS |
|
|
Face Detection (SP)
|
100% |
5003
59.4 IPS |
|
|
Face Detection (HP)
|
100% |
1630
19.4 IPS |
|
|
Face Detection (Q)
|
97% |
10437
124.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6559
50.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
2051
15.8 IPS |
|
|
Depth Estimation (Q)
|
78% |
8621
68.8 IPS |
|
|
Style Transfer (SP)
|
100% |
10412
13.4 IPS |
|
|
Style Transfer (HP)
|
100% |
9959
12.8 IPS |
|
|
Style Transfer (Q)
|
98% |
24405
31.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2022
74.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1712
63.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3192
118.2 IPS |
|
|
Text Classification (SP)
|
100% |
1762
2.35 KIPS |
|
|
Text Classification (HP)
|
100% |
746
996.3 IPS |
|
|
Text Classification (Q)
|
97% |
1660
2.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
2170
37.4 IPS |
|
|
Machine Translation (HP)
|
100% |
717
12.3 IPS |
|
|
Machine Translation (Q)
|
65% |
3085
62.0 IPS |
