GEEKOM Mini IT13
Geekbench ML Score
3043
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 25 2024 10:45 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | GEEKOM Mini IT13 |
| Motherboard | Default string Default string |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i9-13900H |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.60 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 10 |
| L1 Data Cache | 48.0 KB x 10 |
| L2 Cache | 1.25 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% |
1668
312.2 IPS |
|
|
Image Classification (F16)
|
100% |
1636
306.2 IPS |
|
|
Image Classification (I8)
|
99% |
3055
571.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1519
25.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1535
25.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
2179
36.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
5422
6.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
5359
6.49 IPS |
|
|
Pose Estimation (I8)
|
100% |
18342
22.2 IPS |
|
|
Object Detection (F32)
|
100% |
1559
116.4 IPS |
|
|
Object Detection (F16)
|
100% |
1574
117.5 IPS |
|
|
Object Detection (I8)
|
62% |
1501
112.1 IPS |
|
|
Face Detection (F32)
|
100% |
2742
32.6 IPS |
|
|
Face Detection (F16)
|
100% |
2757
32.8 IPS |
|
|
Face Detection (I8)
|
89% |
3471
41.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
6228
48.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
6256
48.5 IPS |
|
|
Depth Estimation (I8)
|
96% |
11727
90.9 IPS |
|
|
Style Transfer (F32)
|
100% |
12520
16.5 IPS |
|
|
Style Transfer (F16)
|
100% |
12667
16.7 IPS |
|
|
Style Transfer (I8)
|
98% |
16873
22.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2747
98.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2816
100.6 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3796
135.6 IPS |
|
|
Text Classification (F32)
|
100% |
1288
1.85 KIPS |
|
|
Text Classification (F16)
|
100% |
1292
1.86 KIPS |
|
|
Text Classification (I8)
|
98% |
416
597.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1579
29.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1597
29.4 IPS |
|
|
Machine Translation (I8)
|
67% |
2315
42.6 IPS |
