GMKtec NucBox_EVO-T1
Geekbench AI Score
3405
Single Precision Score
1502
Half Precision Score
6571
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | fklauber |
| Upload Date | January 14 2026 03:47 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core Ultra 9 285H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | GMKtec NucBox_EVO-T1 |
| Motherboard | GMKtec GMKtec |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 285H |
| Topology | 1 Processor, 16 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2548
473.9 IPS |
|
|
Image Classification (HP)
|
100% |
602
111.9 IPS |
|
|
Image Classification (Q)
|
99% |
6945
1.30 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1909
30.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
900
14.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
7585
123.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
4971
5.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
3290
3.84 IPS |
|
|
Pose Estimation (Q)
|
94% |
17064
20.0 IPS |
|
|
Object Detection (SP)
|
100% |
1435
113.8 IPS |
|
|
Object Detection (HP)
|
100% |
511
40.5 IPS |
|
|
Object Detection (Q)
|
86% |
4207
338.1 IPS |
|
|
Face Detection (SP)
|
100% |
5902
70.1 IPS |
|
|
Face Detection (HP)
|
100% |
1547
18.4 IPS |
|
|
Face Detection (Q)
|
97% |
9507
113.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
7974
61.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
2675
20.6 IPS |
|
|
Depth Estimation (Q)
|
78% |
9368
74.8 IPS |
|
|
Style Transfer (SP)
|
100% |
14371
18.5 IPS |
|
|
Style Transfer (HP)
|
100% |
10713
13.8 IPS |
|
|
Style Transfer (Q)
|
98% |
20509
26.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2527
93.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1917
70.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4757
176.2 IPS |
|
|
Text Classification (SP)
|
100% |
1604
2.14 KIPS |
|
|
Text Classification (HP)
|
100% |
855
1.14 KIPS |
|
|
Text Classification (Q)
|
97% |
1457
1.95 KIPS |
|
|
Machine Translation (SP)
|
100% |
2208
38.0 IPS |
|
|
Machine Translation (HP)
|
100% |
888
15.3 IPS |
|
|
Machine Translation (Q)
|
65% |
3138
63.0 IPS |
