MECHREVO YAOSHI Series
Geekbench AI Score
25038
Single Precision Score
41782
Half Precision Score
19719
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | tobbyng |
| Upload Date | January 31 2026 07:28 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% |
9946
1.85 KIPS |
|
|
Image Classification (HP)
|
100% |
15130
2.81 KIPS |
|
|
Image Classification (Q)
|
100% |
9065
1.69 KIPS |
|
|
Image Segmentation (SP)
|
100% |
18557
300.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
26528
430.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
16473
267.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
150573
175.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
417029
486.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
135809
159.1 IPS |
|
|
Object Detection (SP)
|
100% |
12428
985.8 IPS |
|
|
Object Detection (HP)
|
100% |
19709
1.56 KIPS |
|
|
Object Detection (Q)
|
86% |
10685
858.4 IPS |
|
|
Face Detection (SP)
|
100% |
36062
428.5 IPS |
|
|
Face Detection (HP)
|
100% |
47095
559.6 IPS |
|
|
Face Detection (Q)
|
97% |
30058
358.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
65612
505.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
120059
925.0 IPS |
|
|
Depth Estimation (Q)
|
78% |
51416
410.7 IPS |
|
|
Style Transfer (SP)
|
100% |
237273
305.0 IPS |
|
|
Style Transfer (HP)
|
100% |
782531
1.01 KIPS |
|
|
Style Transfer (Q)
|
98% |
204986
264.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
35611
1.31 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
61624
2.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
28731
1.06 KIPS |
|
|
Text Classification (SP)
|
100% |
2783
3.72 KIPS |
|
|
Text Classification (HP)
|
100% |
3539
4.72 KIPS |
|
|
Text Classification (Q)
|
97% |
1890
2.53 KIPS |
|
|
Machine Translation (SP)
|
100% |
5039
86.8 IPS |
|
|
Machine Translation (HP)
|
100% |
5094
87.8 IPS |
|
|
Machine Translation (Q)
|
70% |
2385
44.7 IPS |
