MECHREVO YAOSHI Series
Geekbench AI Score
27703
Single Precision Score
47553
Half Precision Score
21663
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | tobbyng |
| Upload Date | January 31 2026 02:28 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% |
11670
2.17 KIPS |
|
|
Image Classification (HP)
|
100% |
19359
3.60 KIPS |
|
|
Image Classification (Q)
|
100% |
10487
1.95 KIPS |
|
|
Image Segmentation (SP)
|
100% |
20071
325.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
28693
465.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
18105
294.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
152990
178.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
422157
492.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
133650
156.6 IPS |
|
|
Object Detection (SP)
|
100% |
14229
1.13 KIPS |
|
|
Object Detection (HP)
|
100% |
23388
1.86 KIPS |
|
|
Object Detection (Q)
|
86% |
12015
965.3 IPS |
|
|
Face Detection (SP)
|
100% |
39420
468.4 IPS |
|
|
Face Detection (HP)
|
100% |
56499
671.3 IPS |
|
|
Face Detection (Q)
|
97% |
33782
402.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
68552
528.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
124623
960.1 IPS |
|
|
Depth Estimation (Q)
|
78% |
53661
428.7 IPS |
|
|
Style Transfer (SP)
|
100% |
245956
316.2 IPS |
|
|
Style Transfer (HP)
|
100% |
839900
1.08 KIPS |
|
|
Style Transfer (Q)
|
98% |
209780
270.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39355
1.45 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
68425
2.53 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31790
1.18 KIPS |
|
|
Text Classification (SP)
|
100% |
3568
4.76 KIPS |
|
|
Text Classification (HP)
|
100% |
4648
6.20 KIPS |
|
|
Text Classification (Q)
|
97% |
2231
2.99 KIPS |
|
|
Machine Translation (SP)
|
100% |
5596
96.4 IPS |
|
|
Machine Translation (HP)
|
100% |
5732
98.7 IPS |
|
|
Machine Translation (Q)
|
70% |
2768
51.9 IPS |
