MECHREVO YAOSHI Series
Geekbench AI Score
27792
Single Precision Score
47553
Half Precision Score
21675
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | tobbyng |
| Upload Date | January 31 2026 07:15 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | MECHREVO YAOSHI Series |
| Motherboard | MECHREVO YAOSHI Series-X6AR55xY |
| 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% |
11314
2.10 KIPS |
|
|
Image Classification (HP)
|
100% |
18400
3.42 KIPS |
|
|
Image Classification (Q)
|
100% |
10235
1.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
20041
324.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
28448
461.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
17978
292.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
157568
183.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
450094
525.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
142728
167.2 IPS |
|
|
Object Detection (SP)
|
100% |
13916
1.10 KIPS |
|
|
Object Detection (HP)
|
100% |
22493
1.78 KIPS |
|
|
Object Detection (Q)
|
86% |
11805
948.5 IPS |
|
|
Face Detection (SP)
|
100% |
39756
472.4 IPS |
|
|
Face Detection (HP)
|
100% |
55808
663.1 IPS |
|
|
Face Detection (Q)
|
97% |
33909
404.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
68406
527.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
129888
1.00 KIPS |
|
|
Depth Estimation (Q)
|
78% |
53222
425.2 IPS |
|
|
Style Transfer (SP)
|
100% |
250256
321.7 IPS |
|
|
Style Transfer (HP)
|
100% |
830742
1.07 KIPS |
|
|
Style Transfer (Q)
|
98% |
217267
280.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39586
1.46 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
69545
2.57 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31498
1.17 KIPS |
|
|
Text Classification (SP)
|
100% |
3590
4.79 KIPS |
|
|
Text Classification (HP)
|
100% |
4680
6.25 KIPS |
|
|
Text Classification (Q)
|
97% |
2180
2.92 KIPS |
|
|
Machine Translation (SP)
|
100% |
5717
98.5 IPS |
|
|
Machine Translation (HP)
|
100% |
5693
98.1 IPS |
|
|
Machine Translation (Q)
|
70% |
2742
51.4 IPS |
