GMKtec NucBox_EVO-T1
Geekbench AI Score
1746
Single Precision Score
768
Half Precision Score
7783
Quantized Score
Geekbench AI 1.5.0 for Linux AVX2
Result Information
| User | Oleksandr |
| Upload Date | December 05 2025 01:51 PM |
| Views | 14 |
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 | 62.32 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
871
162.0 IPS |
|
|
Image Classification (HP)
|
100% |
218
40.6 IPS |
|
|
Image Classification (Q)
|
97% |
6563
1.22 KIPS |
|
|
Image Segmentation (SP)
|
100% |
942
15.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
355
5.75 IPS |
|
|
Image Segmentation (Q)
|
99% |
4007
65.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1967
2.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
2491
2.91 IPS |
|
|
Pose Estimation (Q)
|
94% |
23096
27.1 IPS |
|
|
Object Detection (SP)
|
100% |
1096
86.9 IPS |
|
|
Object Detection (HP)
|
100% |
280
22.2 IPS |
|
|
Object Detection (Q)
|
86% |
5784
464.9 IPS |
|
|
Face Detection (SP)
|
100% |
2568
30.5 IPS |
|
|
Face Detection (HP)
|
100% |
438
5.21 IPS |
|
|
Face Detection (Q)
|
97% |
17267
205.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
2791
21.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
1125
8.67 IPS |
|
|
Depth Estimation (Q)
|
78% |
15204
121.3 IPS |
|
|
Style Transfer (SP)
|
100% |
5326
6.85 IPS |
|
|
Style Transfer (HP)
|
100% |
6217
7.99 IPS |
|
|
Style Transfer (Q)
|
98% |
21796
28.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1514
55.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1200
44.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5370
198.8 IPS |
|
|
Text Classification (SP)
|
100% |
1215
1.62 KIPS |
|
|
Text Classification (HP)
|
100% |
525
700.8 IPS |
|
|
Text Classification (Q)
|
97% |
1637
2.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
2122
36.5 IPS |
|
|
Machine Translation (HP)
|
100% |
687
11.8 IPS |
|
|
Machine Translation (Q)
|
65% |
4616
92.7 IPS |
