MAXSUN MS-iCraft Z890 Pacific
Geekbench AI Score
6028
Single Precision Score
9216
Half Precision Score
13786
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| Upload Date | November 01 2024 07:58 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | MAXSUN MS-iCraft Z890 Pacific |
| Motherboard | MAXSUN MS-iCraft Z890 Pacific |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285K |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4074
757.6 IPS |
|
|
Image Classification (HP)
|
100% |
6156
1.14 KIPS |
|
|
Image Classification (Q)
|
100% |
8237
1.53 KIPS |
|
|
Image Segmentation (SP)
|
100% |
4165
67.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
8447
136.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
11804
191.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
12201
14.2 IPS |
|
|
Pose Estimation (HP)
|
99% |
11443
13.4 IPS |
|
|
Pose Estimation (Q)
|
97% |
35217
41.2 IPS |
|
|
Object Detection (SP)
|
100% |
3738
296.5 IPS |
|
|
Object Detection (HP)
|
100% |
5812
461.0 IPS |
|
|
Object Detection (Q)
|
88% |
9153
733.5 IPS |
|
|
Face Detection (SP)
|
100% |
8941
106.2 IPS |
|
|
Face Detection (HP)
|
100% |
16946
201.4 IPS |
|
|
Face Detection (Q)
|
100% |
26100
310.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
12958
99.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
22536
174.2 IPS |
|
|
Depth Estimation (Q)
|
89% |
26010
202.2 IPS |
|
|
Style Transfer (SP)
|
100% |
30572
39.3 IPS |
|
|
Style Transfer (HP)
|
100% |
43280
55.6 IPS |
|
|
Style Transfer (Q)
|
98% |
87448
112.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5341
197.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
9588
354.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
15075
558.3 IPS |
|
|
Text Classification (SP)
|
71% |
1935
2.80 KIPS |
|
|
Text Classification (HP)
|
71% |
2586
3.74 KIPS |
|
|
Text Classification (Q)
|
92% |
2835
3.81 KIPS |
|
|
Machine Translation (SP)
|
100% |
2237
38.5 IPS |
|
|
Machine Translation (HP)
|
96% |
3119
53.9 IPS |
|
|
Machine Translation (Q)
|
100% |
3120
53.7 IPS |
