Micro-Star International Co., Ltd. Prestige 16 AI+ Evo B2VMG
Geekbench AI Score
2994
Single Precision Score
23569
Half Precision Score
34797
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | danm1988 |
| Upload Date | June 08 2025 12:45 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro for Workstations (64-bit) |
| Model | Micro-Star International Co., Ltd. Prestige 16 AI+ Evo B2VMG |
| Motherboard | Micro-Star International Co., Ltd. MS-15A3 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 288V |
| Topology | 1 Processor, 8 Cores |
| Identifier | GenuineIntel Family 6 Model 189 Stepping 1 |
| Base Frequency | 3.30 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1648
306.5 IPS |
|
|
Image Classification (HP)
|
100% |
10657
1.98 KIPS |
|
|
Image Classification (Q)
|
100% |
15040
2.80 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1835
29.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
19388
314.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
31027
503.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
3185
3.72 IPS |
|
|
Pose Estimation (HP)
|
100% |
112148
130.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
219284
256.9 IPS |
|
|
Object Detection (SP)
|
100% |
1795
142.4 IPS |
|
|
Object Detection (HP)
|
100% |
13548
1.07 KIPS |
|
|
Object Detection (Q)
|
87% |
22098
1.77 KIPS |
|
|
Face Detection (SP)
|
100% |
5488
65.2 IPS |
|
|
Face Detection (HP)
|
100% |
36073
428.6 IPS |
|
|
Face Detection (Q)
|
100% |
68740
816.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
4300
33.1 IPS |
|
|
Depth Estimation (HP)
|
93% |
70096
543.0 IPS |
|
|
Depth Estimation (Q)
|
88% |
131322
1.02 KIPS |
|
|
Style Transfer (SP)
|
100% |
9504
12.2 IPS |
|
|
Style Transfer (HP)
|
100% |
216837
278.7 IPS |
|
|
Style Transfer (Q)
|
98% |
370526
477.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2044
75.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31828
1.18 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
50106
1.86 KIPS |
|
|
Text Classification (SP)
|
100% |
2119
2.83 KIPS |
|
|
Text Classification (HP)
|
100% |
2528
3.37 KIPS |
|
|
Text Classification (Q)
|
92% |
1739
2.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
3455
59.5 IPS |
|
|
Machine Translation (HP)
|
100% |
3820
65.8 IPS |
|
|
Machine Translation (Q)
|
100% |
3950
68.0 IPS |
