MECHREVO YAOSHI Series
Geekbench AI Score
27579
Single Precision Score
47361
Half Precision Score
21623
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | tobbyng |
| Upload Date | January 31 2026 02:30 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 (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% |
11657
2.17 KIPS |
|
|
Image Classification (HP)
|
100% |
18898
3.51 KIPS |
|
|
Image Classification (Q)
|
100% |
10482
1.95 KIPS |
|
|
Image Segmentation (SP)
|
100% |
20069
325.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
28681
464.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
18150
295.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
150496
175.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
422592
493.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
133028
155.8 IPS |
|
|
Object Detection (SP)
|
100% |
14206
1.13 KIPS |
|
|
Object Detection (HP)
|
100% |
23098
1.83 KIPS |
|
|
Object Detection (Q)
|
86% |
11913
957.1 IPS |
|
|
Face Detection (SP)
|
100% |
39467
469.0 IPS |
|
|
Face Detection (HP)
|
100% |
56859
675.6 IPS |
|
|
Face Detection (Q)
|
97% |
33608
400.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
68741
529.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
125723
968.6 IPS |
|
|
Depth Estimation (Q)
|
78% |
54149
432.6 IPS |
|
|
Style Transfer (SP)
|
100% |
241051
309.9 IPS |
|
|
Style Transfer (HP)
|
100% |
839257
1.08 KIPS |
|
|
Style Transfer (Q)
|
98% |
213186
274.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39148
1.45 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
68340
2.52 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31632
1.17 KIPS |
|
|
Text Classification (SP)
|
100% |
3592
4.79 KIPS |
|
|
Text Classification (HP)
|
100% |
4628
6.18 KIPS |
|
|
Text Classification (Q)
|
97% |
2185
2.93 KIPS |
|
|
Machine Translation (SP)
|
100% |
5536
95.4 IPS |
|
|
Machine Translation (HP)
|
100% |
5657
97.4 IPS |
|
|
Machine Translation (Q)
|
70% |
2764
51.8 IPS |
