Micro-Star International Co., Ltd. Cyborg 15 B2RWEKG
Geekbench AI Score
2283
Single Precision Score
1130
Half Precision Score
4426
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | September 02 2025 04:11 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) 5 210H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Micro-Star International Co., Ltd. Cyborg 15 B2RWEKG |
| Motherboard | Micro-Star International Co., Ltd. MS-15Q3 |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) 5 210H |
| Topology | 1 Processor, 8 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1670
310.6 IPS |
|
|
Image Classification (HP)
|
100% |
450
83.8 IPS |
|
|
Image Classification (Q)
|
99% |
3694
689.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1004
16.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
743
12.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2271
36.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
3297
3.85 IPS |
|
|
Pose Estimation (HP)
|
100% |
2574
3.00 IPS |
|
|
Pose Estimation (Q)
|
94% |
11746
13.8 IPS |
|
|
Object Detection (SP)
|
100% |
1633
129.5 IPS |
|
|
Object Detection (HP)
|
100% |
545
43.3 IPS |
|
|
Object Detection (Q)
|
86% |
3572
287.1 IPS |
|
|
Face Detection (SP)
|
100% |
4094
48.6 IPS |
|
|
Face Detection (HP)
|
100% |
1303
15.5 IPS |
|
|
Face Detection (Q)
|
97% |
6092
72.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
4426
34.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1668
12.9 IPS |
|
|
Depth Estimation (Q)
|
78% |
9271
74.0 IPS |
|
|
Style Transfer (SP)
|
100% |
8198
10.5 IPS |
|
|
Style Transfer (HP)
|
100% |
6467
8.31 IPS |
|
|
Style Transfer (Q)
|
98% |
15451
19.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1669
61.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1360
50.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2957
109.5 IPS |
|
|
Text Classification (SP)
|
100% |
1174
1.57 KIPS |
|
|
Text Classification (HP)
|
100% |
623
831.0 IPS |
|
|
Text Classification (Q)
|
97% |
1485
1.99 KIPS |
|
|
Machine Translation (SP)
|
100% |
1465
25.2 IPS |
|
|
Machine Translation (HP)
|
100% |
613
10.6 IPS |
|
|
Machine Translation (Q)
|
65% |
2140
43.0 IPS |
