MECHREVO YAOSHI Series
Geekbench AI Score
25374
Single Precision Score
46076
Half Precision Score
19458
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | April 22 2025 01:40 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 Ti Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | MECHREVO YAOSHI Series |
| Motherboard | MECHREVO YAOSHI Series-X6AR55xY |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) 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% |
10408
1.94 KIPS |
|
|
Image Classification (HP)
|
100% |
18362
3.41 KIPS |
|
|
Image Classification (Q)
|
100% |
9477
1.76 KIPS |
|
|
Image Segmentation (SP)
|
100% |
19431
315.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
29018
470.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
17640
286.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
121057
141.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
410260
478.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
107270
125.7 IPS |
|
|
Object Detection (SP)
|
100% |
13717
1.09 KIPS |
|
|
Object Detection (HP)
|
100% |
23170
1.84 KIPS |
|
|
Object Detection (Q)
|
83% |
11338
916.0 IPS |
|
|
Face Detection (SP)
|
100% |
35904
426.6 IPS |
|
|
Face Detection (HP)
|
100% |
54398
646.4 IPS |
|
|
Face Detection (Q)
|
97% |
30733
366.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
60585
466.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
115076
886.6 IPS |
|
|
Depth Estimation (Q)
|
78% |
49509
395.2 IPS |
|
|
Style Transfer (SP)
|
100% |
199816
256.9 IPS |
|
|
Style Transfer (HP)
|
100% |
674019
866.5 IPS |
|
|
Style Transfer (Q)
|
98% |
175611
226.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
34942
1.29 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
68527
2.53 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
26983
999.2 IPS |
|
|
Text Classification (SP)
|
100% |
3658
4.88 KIPS |
|
|
Text Classification (HP)
|
100% |
4722
6.30 KIPS |
|
|
Text Classification (Q)
|
97% |
2252
3.02 KIPS |
|
|
Machine Translation (SP)
|
100% |
5932
102.2 IPS |
|
|
Machine Translation (HP)
|
100% |
6237
107.4 IPS |
|
|
Machine Translation (Q)
|
70% |
2357
44.2 IPS |
