| User | danm1988 |
| Upload Date | July 24 2025 08:10 PM |
| Views | 11 |
| 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 |
| 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 |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1803
335.4 IPS |
|
|
Image Classification (HP)
|
100% |
16240
3.02 KIPS |
|
|
Image Classification (Q)
|
100% |
21601
4.02 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2141
34.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
20407
330.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
32136
521.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
3454
4.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
112513
131.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
235415
275.8 IPS |
|
|
Object Detection (SP)
|
100% |
1855
147.2 IPS |
|
|
Object Detection (HP)
|
100% |
13944
1.11 KIPS |
|
|
Object Detection (Q)
|
88% |
26458
2.12 KIPS |
|
|
Face Detection (SP)
|
100% |
5542
65.8 IPS |
|
|
Face Detection (HP)
|
100% |
38871
461.9 IPS |
|
|
Face Detection (Q)
|
100% |
82805
983.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
4793
36.9 IPS |
|
|
Depth Estimation (HP)
|
93% |
75017
581.1 IPS |
|
|
Depth Estimation (Q)
|
88% |
153014
1.19 KIPS |
|
|
Style Transfer (SP)
|
100% |
10320
13.3 IPS |
|
|
Style Transfer (HP)
|
100% |
228745
294.1 IPS |
|
|
Style Transfer (Q)
|
98% |
429610
554.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2163
79.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
37120
1.37 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
81100
3.00 KIPS |
|
|
Text Classification (SP)
|
100% |
2143
2.86 KIPS |
|
|
Text Classification (HP)
|
100% |
3001
4.01 KIPS |
|
|
Text Classification (Q)
|
92% |
2676
3.59 KIPS |
|
|
Machine Translation (SP)
|
100% |
3594
61.9 IPS |
|
|
Machine Translation (HP)
|
100% |
4030
69.4 IPS |
|
|
Machine Translation (Q)
|
100% |
4129
71.1 IPS |