Micro Computer (HK) Tech Limited MS-02-Ultra
Geekbench ML Score
3552
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | January 02 2026 03:42 PM |
| Views | 11 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro Computer (HK) Tech Limited MS-02-Ultra |
| Motherboard | Meigao Innovation Technology (Shen Zhen) Co., Ltd ARWSA |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285HX |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 2.80 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| L1 Instruction Cache | 64.0 KB x 12 |
| L1 Data Cache | 48.0 KB x 12 |
| L2 Cache | 3.00 MB x 3 |
| L3 Cache | 36.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2164
405.0 IPS |
|
|
Image Classification (F16)
|
100% |
2193
410.4 IPS |
|
|
Image Classification (I8)
|
100% |
1581
295.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
2765
46.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
2799
46.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1927
32.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
7957
9.64 IPS |
|
|
Pose Estimation (F16)
|
100% |
8098
9.81 IPS |
|
|
Pose Estimation (I8)
|
100% |
7052
8.54 IPS |
|
|
Object Detection (F32)
|
100% |
2293
171.2 IPS |
|
|
Object Detection (F16)
|
100% |
2313
172.7 IPS |
|
|
Object Detection (I8)
|
54% |
1716
128.1 IPS |
|
|
Face Detection (F32)
|
100% |
4254
50.6 IPS |
|
|
Face Detection (F16)
|
100% |
4275
50.8 IPS |
|
|
Face Detection (I8)
|
89% |
2682
31.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
9330
72.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
9266
71.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
6761
52.4 IPS |
|
|
Style Transfer (F32)
|
100% |
26059
34.3 IPS |
|
|
Style Transfer (F16)
|
100% |
26193
34.5 IPS |
|
|
Style Transfer (I8)
|
98% |
19786
26.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4939
176.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4789
171.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3199
114.2 IPS |
|
|
Text Classification (F32)
|
100% |
1054
1.52 KIPS |
|
|
Text Classification (F16)
|
100% |
1036
1.49 KIPS |
|
|
Text Classification (I8)
|
98% |
620
890.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1979
36.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1951
35.9 IPS |
|
|
Machine Translation (I8)
|
70% |
934
17.2 IPS |
