MECHREVO YAOSHI Series
Geekbench AI Score
27769
Single Precision Score
47215
Half Precision Score
21665
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | tobbyng |
| Upload Date | January 31 2026 07:13 AM |
| Views | 7 |
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% |
11274
2.10 KIPS |
|
|
Image Classification (HP)
|
100% |
17715
3.29 KIPS |
|
|
Image Classification (Q)
|
100% |
10296
1.91 KIPS |
|
|
Image Segmentation (SP)
|
100% |
20041
324.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
28291
458.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
18129
294.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
158318
184.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
450627
525.8 IPS |
|
|
Pose Estimation (Q)
|
96% |
142311
166.7 IPS |
|
|
Object Detection (SP)
|
100% |
13755
1.09 KIPS |
|
|
Object Detection (HP)
|
100% |
22379
1.78 KIPS |
|
|
Object Detection (Q)
|
86% |
11719
941.5 IPS |
|
|
Face Detection (SP)
|
100% |
39773
472.6 IPS |
|
|
Face Detection (HP)
|
100% |
56122
666.9 IPS |
|
|
Face Detection (Q)
|
97% |
34072
406.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
68803
530.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
129817
1.00 KIPS |
|
|
Depth Estimation (Q)
|
78% |
53535
427.7 IPS |
|
|
Style Transfer (SP)
|
100% |
251667
323.5 IPS |
|
|
Style Transfer (HP)
|
100% |
825593
1.06 KIPS |
|
|
Style Transfer (Q)
|
98% |
214590
276.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39450
1.46 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
69230
2.56 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31751
1.18 KIPS |
|
|
Text Classification (SP)
|
100% |
3600
4.81 KIPS |
|
|
Text Classification (HP)
|
100% |
4582
6.12 KIPS |
|
|
Text Classification (Q)
|
97% |
2190
2.93 KIPS |
|
|
Machine Translation (SP)
|
100% |
5666
97.6 IPS |
|
|
Machine Translation (HP)
|
100% |
5710
98.3 IPS |
|
|
Machine Translation (Q)
|
70% |
2690
50.4 IPS |
