Micro-Star International Co., Ltd. Prestige 16 AI+ Evo B2VMG
Geekbench AI Score
11087
Single Precision Score
26611
Half Precision Score
29466
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | danm1988 |
| Upload Date | July 12 2025 12:30 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) Graphics (iGPU) |
| 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 |
| 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% |
7474
1.39 KIPS |
|
|
Image Classification (HP)
|
100% |
15202
2.83 KIPS |
|
|
Image Classification (Q)
|
100% |
17621
3.28 KIPS |
|
|
Image Segmentation (SP)
|
100% |
9909
160.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
25496
413.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
30432
493.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
23457
27.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
134947
157.5 IPS |
|
|
Pose Estimation (Q)
|
97% |
264822
310.0 IPS |
|
|
Object Detection (SP)
|
100% |
6670
529.1 IPS |
|
|
Object Detection (HP)
|
100% |
15168
1.20 KIPS |
|
|
Object Detection (Q)
|
88% |
15680
1.26 KIPS |
|
|
Face Detection (SP)
|
100% |
13395
159.2 IPS |
|
|
Face Detection (HP)
|
100% |
28518
338.8 IPS |
|
|
Face Detection (Q)
|
100% |
35968
427.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
24479
188.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
59267
456.6 IPS |
|
|
Depth Estimation (Q)
|
89% |
67867
527.8 IPS |
|
|
Style Transfer (SP)
|
100% |
54123
69.6 IPS |
|
|
Style Transfer (HP)
|
100% |
159582
205.1 IPS |
|
|
Style Transfer (Q)
|
98% |
165528
213.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9855
363.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
27306
1.01 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
27333
1.01 KIPS |
|
|
Text Classification (SP)
|
100% |
4271
5.70 KIPS |
|
|
Text Classification (HP)
|
100% |
5273
7.04 KIPS |
|
|
Text Classification (Q)
|
92% |
3457
4.64 KIPS |
|
|
Machine Translation (SP)
|
100% |
3245
55.9 IPS |
|
|
Machine Translation (HP)
|
100% |
5781
99.6 IPS |
|
|
Machine Translation (Q)
|
100% |
5804
100.0 IPS |
