GEEKOM IT15
Geekbench ML Score
3685
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 01 2025 05:18 PM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | GEEKOM IT15 |
| Motherboard | GEEKOM IT15 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) 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 |
| L1 Instruction Cache | 64.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 3.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1861
348.3 IPS |
|
|
Image Classification (F16)
|
100% |
1856
347.3 IPS |
|
|
Image Classification (I8)
|
99% |
3221
602.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1583
26.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1553
25.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
2810
46.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
6280
7.61 IPS |
|
|
Pose Estimation (F16)
|
100% |
6321
7.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
25021
30.3 IPS |
|
|
Object Detection (F32)
|
100% |
1733
129.3 IPS |
|
|
Object Detection (F16)
|
100% |
1699
126.8 IPS |
|
|
Object Detection (I8)
|
62% |
1624
121.3 IPS |
|
|
Face Detection (F32)
|
100% |
4029
47.9 IPS |
|
|
Face Detection (F16)
|
100% |
3980
47.3 IPS |
|
|
Face Detection (I8)
|
89% |
4452
52.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
7157
55.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
7049
54.7 IPS |
|
|
Depth Estimation (I8)
|
96% |
14246
110.5 IPS |
|
|
Style Transfer (F32)
|
100% |
17130
22.5 IPS |
|
|
Style Transfer (F16)
|
100% |
17150
22.6 IPS |
|
|
Style Transfer (I8)
|
98% |
23098
30.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3004
107.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2828
101.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
5050
180.4 IPS |
|
|
Text Classification (F32)
|
100% |
1068
1.53 KIPS |
|
|
Text Classification (F16)
|
100% |
1094
1.57 KIPS |
|
|
Text Classification (I8)
|
98% |
1057
1.52 KIPS |
|
|
Machine Translation (F32)
|
100% |
2003
36.9 IPS |
|
|
Machine Translation (F16)
|
100% |
2036
37.5 IPS |
|
|
Machine Translation (I8)
|
67% |
3589
66.0 IPS |
