HP HP Pavilion Laptop 15-eg1xxx
Geekbench ML Score
1911
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 17 2024 02:39 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | HP HP Pavilion Laptop 15-eg1xxx |
| Motherboard | HP 898A |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-1155G7 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 140 Stepping 2 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 4 |
| L1 Data Cache | 48.0 KB x 4 |
| L2 Cache | 1.25 MB x 4 |
| L3 Cache | 8.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 12.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Iris(R) Xe Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
915
171.2 IPS |
|
|
Image Classification (F16)
|
100% |
920
172.1 IPS |
|
|
Image Classification (I8)
|
100% |
747
139.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1387
23.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1377
23.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
977
16.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
7695
9.32 IPS |
|
|
Pose Estimation (F16)
|
100% |
7806
9.45 IPS |
|
|
Pose Estimation (I8)
|
100% |
4594
5.56 IPS |
|
|
Object Detection (F32)
|
100% |
1032
77.0 IPS |
|
|
Object Detection (F16)
|
100% |
1010
75.4 IPS |
|
|
Object Detection (I8)
|
54% |
803
60.0 IPS |
|
|
Face Detection (F32)
|
100% |
1836
21.8 IPS |
|
|
Face Detection (F16)
|
100% |
1833
21.8 IPS |
|
|
Face Detection (I8)
|
89% |
1256
14.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
4569
35.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
4497
34.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
3284
25.5 IPS |
|
|
Style Transfer (F32)
|
100% |
18897
24.9 IPS |
|
|
Style Transfer (F16)
|
100% |
18866
24.8 IPS |
|
|
Style Transfer (I8)
|
98% |
11837
15.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2893
103.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2867
102.4 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
1276
45.6 IPS |
|
|
Text Classification (F32)
|
100% |
836
1.20 KIPS |
|
|
Text Classification (F16)
|
100% |
831
1.19 KIPS |
|
|
Text Classification (I8)
|
98% |
377
542.4 IPS |
|
|
Machine Translation (F32)
|
100% |
819
15.1 IPS |
|
|
Machine Translation (F16)
|
100% |
820
15.1 IPS |
|
|
Machine Translation (I8)
|
70% |
456
8.40 IPS |
