Micro-Star International Co., Ltd. PRO LNL Cubi NUC AI+ 2M (MS-B206)
Geekbench ML Score
2385
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 17 2025 11:26 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. PRO LNL Cubi NUC AI+ 2M (MS-B206) |
| Motherboard | Micro-Star International Co., Ltd. MS-B2061 |
| Power Plan | Ultimative Leistung |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 258V |
| Topology | 1 Processor, 8 Cores |
| Identifier | GenuineIntel Family 6 Model 189 Stepping 1 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 64.0 KB x 4 |
| L1 Data Cache | 48.0 KB x 4 |
| L2 Cache | 2.50 MB x 1 |
| L3 Cache | 12.0 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% |
1107
207.1 IPS |
|
|
Image Classification (F16)
|
100% |
1089
203.8 IPS |
|
|
Image Classification (I8)
|
99% |
2184
408.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1221
20.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1103
18.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
2116
35.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
3443
4.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
3090
3.74 IPS |
|
|
Pose Estimation (I8)
|
100% |
13048
15.8 IPS |
|
|
Object Detection (F32)
|
100% |
1246
93.0 IPS |
|
|
Object Detection (F16)
|
100% |
1159
86.5 IPS |
|
|
Object Detection (I8)
|
62% |
1162
86.8 IPS |
|
|
Face Detection (F32)
|
100% |
2921
34.7 IPS |
|
|
Face Detection (F16)
|
100% |
2652
31.5 IPS |
|
|
Face Detection (I8)
|
89% |
3167
37.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
4184
32.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
3807
29.5 IPS |
|
|
Depth Estimation (I8)
|
96% |
9018
69.9 IPS |
|
|
Style Transfer (F32)
|
100% |
8422
11.1 IPS |
|
|
Style Transfer (F16)
|
100% |
9281
12.2 IPS |
|
|
Style Transfer (I8)
|
98% |
15792
20.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1835
65.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1906
68.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3347
119.5 IPS |
|
|
Text Classification (F32)
|
100% |
942
1.35 KIPS |
|
|
Text Classification (F16)
|
100% |
872
1.25 KIPS |
|
|
Text Classification (I8)
|
98% |
798
1.15 KIPS |
|
|
Machine Translation (F32)
|
100% |
1412
26.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1363
25.1 IPS |
|
|
Machine Translation (I8)
|
67% |
1904
35.0 IPS |
