GMKtec NucBox_EVO-T1
Geekbench AI Score
1752
Single Precision Score
768
Half Precision Score
7792
Quantized Score
Geekbench AI 1.5.0 for Linux AVX2
Result Information
| User | Oleksandr |
| Upload Date | December 03 2025 06:11 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 285H |
| System Information | |
|---|---|
| Operating System | Ubuntu 24.04.3 LTS |
| Model | GMKtec NucBox_EVO-T1 |
| Motherboard | GMKtec GMKtec |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 285H |
| Topology | 1 Processor, 16 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 5.40 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 93.82 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
864
160.7 IPS |
|
|
Image Classification (HP)
|
100% |
220
40.9 IPS |
|
|
Image Classification (Q)
|
97% |
6580
1.23 KIPS |
|
|
Image Segmentation (SP)
|
100% |
949
15.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
356
5.77 IPS |
|
|
Image Segmentation (Q)
|
99% |
4011
65.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2010
2.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
2483
2.90 IPS |
|
|
Pose Estimation (Q)
|
94% |
23301
27.3 IPS |
|
|
Object Detection (SP)
|
100% |
1089
86.3 IPS |
|
|
Object Detection (HP)
|
100% |
281
22.3 IPS |
|
|
Object Detection (Q)
|
86% |
5819
467.7 IPS |
|
|
Face Detection (SP)
|
100% |
2625
31.2 IPS |
|
|
Face Detection (HP)
|
100% |
436
5.18 IPS |
|
|
Face Detection (Q)
|
97% |
17321
206.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
2772
21.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
1129
8.70 IPS |
|
|
Depth Estimation (Q)
|
78% |
15276
121.9 IPS |
|
|
Style Transfer (SP)
|
100% |
5338
6.86 IPS |
|
|
Style Transfer (HP)
|
100% |
6199
7.97 IPS |
|
|
Style Transfer (Q)
|
98% |
21861
28.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1512
55.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1193
44.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5335
197.6 IPS |
|
|
Text Classification (SP)
|
100% |
1227
1.64 KIPS |
|
|
Text Classification (HP)
|
100% |
529
706.0 IPS |
|
|
Text Classification (Q)
|
97% |
1636
2.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
2116
36.4 IPS |
|
|
Machine Translation (HP)
|
100% |
686
11.8 IPS |
|
|
Machine Translation (Q)
|
65% |
4568
91.8 IPS |
