GIGABYTE AORUS Master 16 BYH
Geekbench AI Score
25250
Single Precision Score
42259
Half Precision Score
20071
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | May 04 2025 05:13 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 Laptop GPU |
| 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(R) Core(TM) 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% |
10767
2.00 KIPS |
|
|
Image Classification (HP)
|
100% |
17422
3.24 KIPS |
|
|
Image Classification (Q)
|
100% |
9658
1.80 KIPS |
|
|
Image Segmentation (SP)
|
100% |
16805
272.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
23670
383.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
15514
252.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
145360
169.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
369054
430.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
132123
154.8 IPS |
|
|
Object Detection (SP)
|
100% |
13202
1.05 KIPS |
|
|
Object Detection (HP)
|
100% |
22189
1.76 KIPS |
|
|
Object Detection (Q)
|
86% |
11322
909.7 IPS |
|
|
Face Detection (SP)
|
100% |
35853
426.0 IPS |
|
|
Face Detection (HP)
|
100% |
48562
577.0 IPS |
|
|
Face Detection (Q)
|
97% |
31753
378.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
63581
489.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
116169
895.0 IPS |
|
|
Depth Estimation (Q)
|
78% |
51192
408.9 IPS |
|
|
Style Transfer (SP)
|
100% |
225605
290.0 IPS |
|
|
Style Transfer (HP)
|
100% |
702068
902.5 IPS |
|
|
Style Transfer (Q)
|
98% |
199363
257.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
37548
1.39 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
64872
2.40 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
29913
1.11 KIPS |
|
|
Text Classification (SP)
|
100% |
3239
4.32 KIPS |
|
|
Text Classification (HP)
|
100% |
4155
5.55 KIPS |
|
|
Text Classification (Q)
|
97% |
1977
2.65 KIPS |
|
|
Machine Translation (SP)
|
100% |
4852
83.6 IPS |
|
|
Machine Translation (HP)
|
100% |
5039
86.8 IPS |
|
|
Machine Translation (Q)
|
70% |
2470
46.3 IPS |
