MECHREVO YAOSHI Series
Geekbench AI Score
24833
Single Precision Score
41551
Half Precision Score
19925
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | tobbyng |
| Upload Date | January 31 2026 07:30 AM |
| Views | 6 |
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% |
9787
1.82 KIPS |
|
|
Image Classification (HP)
|
100% |
15485
2.88 KIPS |
|
|
Image Classification (Q)
|
100% |
9166
1.70 KIPS |
|
|
Image Segmentation (SP)
|
100% |
18043
292.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
26060
422.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
17212
279.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
147908
172.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
416851
486.4 IPS |
|
|
Pose Estimation (Q)
|
96% |
135174
158.3 IPS |
|
|
Object Detection (SP)
|
100% |
12276
973.8 IPS |
|
|
Object Detection (HP)
|
100% |
19643
1.56 KIPS |
|
|
Object Detection (Q)
|
86% |
10893
875.2 IPS |
|
|
Face Detection (SP)
|
100% |
33825
401.9 IPS |
|
|
Face Detection (HP)
|
100% |
47151
560.3 IPS |
|
|
Face Detection (Q)
|
97% |
29828
355.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
65421
504.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
118822
915.5 IPS |
|
|
Depth Estimation (Q)
|
78% |
51670
412.8 IPS |
|
|
Style Transfer (SP)
|
100% |
240921
309.7 IPS |
|
|
Style Transfer (HP)
|
100% |
747491
960.9 IPS |
|
|
Style Transfer (Q)
|
98% |
204714
264.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
36406
1.34 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
62611
2.31 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
30107
1.11 KIPS |
|
|
Text Classification (SP)
|
100% |
2899
3.87 KIPS |
|
|
Text Classification (HP)
|
100% |
3453
4.61 KIPS |
|
|
Text Classification (Q)
|
97% |
1861
2.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
4945
85.2 IPS |
|
|
Machine Translation (HP)
|
100% |
5128
88.3 IPS |
|
|
Machine Translation (Q)
|
70% |
2402
45.1 IPS |
