Micro-Star International Co., Ltd. Cyborg 15 B2RWEKG
Geekbench ML Score
10155
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | November 14 2025 02:53 AM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Micro-Star International Co., Ltd. Cyborg 15 B2RWEKG |
| Motherboard | Micro-Star International Co., Ltd. MS-15Q3 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) 7 240H |
| Topology | 1 Processor, 10 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 1.25 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5050 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3917
733.0 IPS |
|
|
Image Classification (F16)
|
100% |
3923
734.2 IPS |
|
|
Image Classification (I8)
|
100% |
4611
862.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
7562
126.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
7556
126.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
6882
114.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
53234
64.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
56267
68.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
51595
62.5 IPS |
|
|
Object Detection (F32)
|
100% |
4000
298.6 IPS |
|
|
Object Detection (F16)
|
100% |
4319
322.5 IPS |
|
|
Object Detection (I8)
|
60% |
3871
289.0 IPS |
|
|
Face Detection (F32)
|
100% |
12895
153.3 IPS |
|
|
Face Detection (F16)
|
100% |
13235
157.4 IPS |
|
|
Face Detection (I8)
|
89% |
11806
140.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
27096
210.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
29328
227.4 IPS |
|
|
Depth Estimation (I8)
|
94% |
23786
184.5 IPS |
|
|
Style Transfer (F32)
|
100% |
89075
117.2 IPS |
|
|
Style Transfer (F16)
|
100% |
87670
115.3 IPS |
|
|
Style Transfer (I8)
|
98% |
71931
94.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
13733
490.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12199
435.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
11826
422.3 IPS |
|
|
Text Classification (F32)
|
100% |
2480
3.56 KIPS |
|
|
Text Classification (F16)
|
100% |
2660
3.82 KIPS |
|
|
Text Classification (I8)
|
98% |
1438
2.07 KIPS |
|
|
Machine Translation (F32)
|
100% |
2914
53.6 IPS |
|
|
Machine Translation (F16)
|
100% |
2815
51.8 IPS |
|
|
Machine Translation (I8)
|
70% |
1675
30.8 IPS |
