MECHREVO YAOSHI Series
Geekbench AI Score
27518
Single Precision Score
47452
Half Precision Score
21738
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | tobbyng |
| Upload Date | January 31 2026 02:32 AM |
| Views | 4 |
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% |
11663
2.17 KIPS |
|
|
Image Classification (HP)
|
100% |
19237
3.58 KIPS |
|
|
Image Classification (Q)
|
100% |
10516
1.96 KIPS |
|
|
Image Segmentation (SP)
|
100% |
20120
326.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
28819
467.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
18133
294.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
150797
176.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
424391
495.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
135130
158.3 IPS |
|
|
Object Detection (SP)
|
100% |
13606
1.08 KIPS |
|
|
Object Detection (HP)
|
100% |
22926
1.82 KIPS |
|
|
Object Detection (Q)
|
86% |
11637
934.9 IPS |
|
|
Face Detection (SP)
|
100% |
38498
457.4 IPS |
|
|
Face Detection (HP)
|
100% |
55455
658.9 IPS |
|
|
Face Detection (Q)
|
97% |
33575
400.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
68852
530.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
122227
941.7 IPS |
|
|
Depth Estimation (Q)
|
78% |
54492
435.3 IPS |
|
|
Style Transfer (SP)
|
100% |
245372
315.4 IPS |
|
|
Style Transfer (HP)
|
100% |
835462
1.07 KIPS |
|
|
Style Transfer (Q)
|
98% |
220094
283.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39544
1.46 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
72384
2.67 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31989
1.18 KIPS |
|
|
Text Classification (SP)
|
100% |
3646
4.87 KIPS |
|
|
Text Classification (HP)
|
100% |
4570
6.10 KIPS |
|
|
Text Classification (Q)
|
97% |
2231
2.99 KIPS |
|
|
Machine Translation (SP)
|
100% |
5516
95.0 IPS |
|
|
Machine Translation (HP)
|
100% |
5729
98.7 IPS |
|
|
Machine Translation (Q)
|
70% |
2735
51.3 IPS |
