ECS MTLH-MINI
Geekbench AI Score
3145
Single Precision Score
1280
Half Precision Score
5715
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | December 21 2024 04:32 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core Ultra 7 155H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | ECS MTLH-MINI |
| Motherboard | ECS MTLH-MINI |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 7 155H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2385
443.5 IPS |
|
|
Image Classification (HP)
|
100% |
487
90.5 IPS |
|
|
Image Classification (Q)
|
99% |
4908
915.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1166
18.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
763
12.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
2940
47.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
5436
6.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
3537
4.13 IPS |
|
|
Pose Estimation (Q)
|
94% |
20347
23.9 IPS |
|
|
Object Detection (SP)
|
100% |
2333
185.0 IPS |
|
|
Object Detection (HP)
|
100% |
549
43.5 IPS |
|
|
Object Detection (Q)
|
86% |
5267
423.3 IPS |
|
|
Face Detection (SP)
|
100% |
6198
73.6 IPS |
|
|
Face Detection (HP)
|
100% |
1398
16.6 IPS |
|
|
Face Detection (Q)
|
97% |
7634
91.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6965
53.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
1805
13.9 IPS |
|
|
Depth Estimation (Q)
|
78% |
13057
104.2 IPS |
|
|
Style Transfer (SP)
|
100% |
12721
16.4 IPS |
|
|
Style Transfer (HP)
|
100% |
8695
11.2 IPS |
|
|
Style Transfer (Q)
|
98% |
16438
21.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2372
87.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1704
62.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3681
136.3 IPS |
|
|
Text Classification (SP)
|
100% |
1284
1.71 KIPS |
|
|
Text Classification (HP)
|
100% |
652
869.8 IPS |
|
|
Text Classification (Q)
|
97% |
1486
1.99 KIPS |
|
|
Machine Translation (SP)
|
100% |
1606
27.7 IPS |
|
|
Machine Translation (HP)
|
100% |
675
11.6 IPS |
|
|
Machine Translation (Q)
|
65% |
2686
54.0 IPS |
