Micro-Star International Co., Ltd. Prestige 16 AI+ Evo B2VMG
Geekbench AI Score
11294
Single Precision Score
27212
Half Precision Score
30457
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | danm1988 |
| Upload Date | June 29 2025 03:13 AM |
| Views | 8 |
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% |
7075
1.32 KIPS |
|
|
Image Classification (HP)
|
100% |
14195
2.64 KIPS |
|
|
Image Classification (Q)
|
100% |
17101
3.18 KIPS |
|
|
Image Segmentation (SP)
|
100% |
9608
155.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
25261
409.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
30067
487.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
24401
28.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
136305
159.0 IPS |
|
|
Pose Estimation (Q)
|
97% |
266287
311.8 IPS |
|
|
Object Detection (SP)
|
100% |
7044
558.7 IPS |
|
|
Object Detection (HP)
|
100% |
16857
1.34 KIPS |
|
|
Object Detection (Q)
|
88% |
16380
1.31 KIPS |
|
|
Face Detection (SP)
|
100% |
13496
160.4 IPS |
|
|
Face Detection (HP)
|
100% |
29538
351.0 IPS |
|
|
Face Detection (Q)
|
100% |
37484
445.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
25741
198.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
59568
458.9 IPS |
|
|
Depth Estimation (Q)
|
89% |
70139
545.4 IPS |
|
|
Style Transfer (SP)
|
100% |
55838
71.8 IPS |
|
|
Style Transfer (HP)
|
100% |
164636
211.6 IPS |
|
|
Style Transfer (Q)
|
98% |
166545
214.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
10100
372.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
28896
1.07 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31611
1.17 KIPS |
|
|
Text Classification (SP)
|
100% |
4470
5.97 KIPS |
|
|
Text Classification (HP)
|
100% |
5526
7.38 KIPS |
|
|
Text Classification (Q)
|
92% |
3493
4.69 KIPS |
|
|
Machine Translation (SP)
|
100% |
3300
56.8 IPS |
|
|
Machine Translation (HP)
|
100% |
5842
100.6 IPS |
|
|
Machine Translation (Q)
|
100% |
6336
109.1 IPS |
