GMKtec NucBox_EVO-X2
Geekbench AI Score
6620
Single Precision Score
2468
Half Precision Score
12015
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | wpopelier |
| Upload Date | August 19 2025 02:15 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen AI Max+ 395 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | GMKtec NucBox_EVO-X2 |
| Motherboard | GMKtec GMKtec |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen AI Max+ 395 |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 26 Model 112 Stepping 0 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 128.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6270
1.17 KIPS |
|
|
Image Classification (HP)
|
100% |
763
141.9 IPS |
|
|
Image Classification (Q)
|
99% |
13464
2.51 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1302
21.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1110
18.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
17184
279.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
15867
18.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
12148
14.2 IPS |
|
|
Pose Estimation (Q)
|
94% |
50960
59.8 IPS |
|
|
Object Detection (SP)
|
100% |
5082
403.1 IPS |
|
|
Object Detection (HP)
|
100% |
951
75.4 IPS |
|
|
Object Detection (Q)
|
86% |
13774
1.11 KIPS |
|
|
Face Detection (SP)
|
100% |
12256
145.6 IPS |
|
|
Face Detection (HP)
|
100% |
2043
24.3 IPS |
|
|
Face Detection (Q)
|
97% |
14027
167.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
16323
125.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
3217
24.8 IPS |
|
|
Depth Estimation (Q)
|
78% |
12161
97.0 IPS |
|
|
Style Transfer (SP)
|
100% |
32488
41.8 IPS |
|
|
Style Transfer (HP)
|
100% |
27696
35.6 IPS |
|
|
Style Transfer (Q)
|
98% |
52559
67.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4761
175.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3449
127.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5430
201.1 IPS |
|
|
Text Classification (SP)
|
100% |
2593
3.46 KIPS |
|
|
Text Classification (HP)
|
100% |
1186
1.58 KIPS |
|
|
Text Classification (Q)
|
97% |
1802
2.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
3061
52.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1151
19.8 IPS |
|
|
Machine Translation (Q)
|
65% |
4404
88.5 IPS |
