GIGABYTE AORUS Master 16 BYH
Geekbench AI Score
7219
Single Precision Score
10066
Half Precision Score
15446
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | November 12 2025 06:32 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | GIGABYTE AORUS Master 16 BYH |
| Motherboard | GIGABYTE AORUS Master 16 BYH |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 275HX |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4353
809.5 IPS |
|
|
Image Classification (HP)
|
100% |
7329
1.36 KIPS |
|
|
Image Classification (Q)
|
100% |
10026
1.86 KIPS |
|
|
Image Segmentation (SP)
|
100% |
6609
107.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2944
47.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
3990
64.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
10426
12.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
34318
40.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
75519
88.5 IPS |
|
|
Object Detection (SP)
|
100% |
4452
353.1 IPS |
|
|
Object Detection (HP)
|
100% |
6179
490.2 IPS |
|
|
Object Detection (Q)
|
87% |
10231
821.1 IPS |
|
|
Face Detection (SP)
|
100% |
13571
161.3 IPS |
|
|
Face Detection (HP)
|
100% |
16940
201.3 IPS |
|
|
Face Detection (Q)
|
100% |
29142
346.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
11674
89.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
18671
143.8 IPS |
|
|
Depth Estimation (Q)
|
88% |
34544
268.8 IPS |
|
|
Style Transfer (SP)
|
100% |
24014
30.9 IPS |
|
|
Style Transfer (HP)
|
100% |
52393
67.4 IPS |
|
|
Style Transfer (Q)
|
98% |
96941
125.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
6266
231.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
14456
533.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
26266
972.7 IPS |
|
|
Text Classification (SP)
|
100% |
3628
4.84 KIPS |
|
|
Text Classification (HP)
|
100% |
2194
2.93 KIPS |
|
|
Text Classification (Q)
|
92% |
2174
2.92 KIPS |
|
|
Machine Translation (SP)
|
100% |
3331
57.4 IPS |
|
|
Machine Translation (HP)
|
100% |
4443
76.5 IPS |
|
|
Machine Translation (Q)
|
100% |
4489
77.3 IPS |
