GEEKOM IT15
Geekbench ML Score
3659
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 01 2025 03:15 PM |
| Views | 3 |
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% |
1821
340.8 IPS |
|
|
Image Classification (F16)
|
100% |
1809
338.6 IPS |
|
|
Image Classification (I8)
|
99% |
3066
573.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1593
26.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1591
26.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
2770
46.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
6524
7.90 IPS |
|
|
Pose Estimation (F16)
|
100% |
6315
7.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
24892
30.1 IPS |
|
|
Object Detection (F32)
|
100% |
1680
125.5 IPS |
|
|
Object Detection (F16)
|
100% |
1687
125.9 IPS |
|
|
Object Detection (I8)
|
62% |
1588
118.5 IPS |
|
|
Face Detection (F32)
|
100% |
3982
47.3 IPS |
|
|
Face Detection (F16)
|
100% |
3914
46.5 IPS |
|
|
Face Detection (I8)
|
89% |
4539
54.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
7220
56.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
7158
55.5 IPS |
|
|
Depth Estimation (I8)
|
96% |
13815
107.1 IPS |
|
|
Style Transfer (F32)
|
100% |
17389
22.9 IPS |
|
|
Style Transfer (F16)
|
100% |
17392
22.9 IPS |
|
|
Style Transfer (I8)
|
98% |
23164
30.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2720
97.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2979
106.4 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4950
176.8 IPS |
|
|
Text Classification (F32)
|
100% |
1071
1.54 KIPS |
|
|
Text Classification (F16)
|
100% |
1065
1.53 KIPS |
|
|
Text Classification (I8)
|
98% |
1065
1.53 KIPS |
|
|
Machine Translation (F32)
|
100% |
2023
37.2 IPS |
|
|
Machine Translation (F16)
|
100% |
2023
37.2 IPS |
|
|
Machine Translation (I8)
|
67% |
3461
63.7 IPS |
