Maxsun MS-Terminator Z890-A
Geekbench AI Score
4237
Single Precision Score
9353
Half Precision Score
14078
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | December 25 2024 05:10 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | Maxsun MS-Terminator Z890-A |
| Motherboard | Maxsun MS-Terminator Z890-A |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 5 245KF |
| Topology | 1 Processor, 14 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 4.20 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2816
523.7 IPS |
|
|
Image Classification (HP)
|
100% |
6726
1.25 KIPS |
|
|
Image Classification (Q)
|
100% |
9234
1.72 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3256
52.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2752
44.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
3623
58.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
4421
5.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
33652
39.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
72364
84.8 IPS |
|
|
Object Detection (SP)
|
100% |
2630
208.6 IPS |
|
|
Object Detection (HP)
|
100% |
5625
446.2 IPS |
|
|
Object Detection (Q)
|
87% |
8773
704.1 IPS |
|
|
Face Detection (SP)
|
100% |
8287
98.5 IPS |
|
|
Face Detection (HP)
|
100% |
15286
181.6 IPS |
|
|
Face Detection (Q)
|
100% |
24707
293.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6277
48.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
18063
139.2 IPS |
|
|
Depth Estimation (Q)
|
88% |
33804
263.0 IPS |
|
|
Style Transfer (SP)
|
100% |
14919
19.2 IPS |
|
|
Style Transfer (HP)
|
100% |
50874
65.4 IPS |
|
|
Style Transfer (Q)
|
98% |
93618
120.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3021
111.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
13690
505.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
24291
899.6 IPS |
|
|
Text Classification (SP)
|
100% |
3043
4.06 KIPS |
|
|
Text Classification (HP)
|
100% |
2239
2.99 KIPS |
|
|
Text Classification (Q)
|
92% |
2241
3.01 KIPS |
|
|
Machine Translation (SP)
|
100% |
2452
42.2 IPS |
|
|
Machine Translation (HP)
|
100% |
3399
58.6 IPS |
|
|
Machine Translation (Q)
|
100% |
3384
58.3 IPS |
