Dynabook Inc. PORTEGE X40L-M
Geekbench ML Score
2874
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | May 08 2024 01:59 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Dynabook Inc. PORTEGE X40L-M |
| Motherboard | Dynabook Inc. OK0123/0000 |
| Power Plan | dynabook standard |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 7 165H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 1.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 11 |
| L1 Data Cache | 48.0 KB x 11 |
| L2 Cache | 2.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Arc(TM) Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1371
256.6 IPS |
|
|
Image Classification (F16)
|
100% |
1374
257.1 IPS |
|
|
Image Classification (I8)
|
100% |
1220
228.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1485
24.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1481
24.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1335
22.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
13420
16.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
11533
14.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
11973
14.5 IPS |
|
|
Object Detection (F32)
|
100% |
1234
92.2 IPS |
|
|
Object Detection (F16)
|
100% |
1265
94.5 IPS |
|
|
Object Detection (I8)
|
54% |
1103
82.4 IPS |
|
|
Face Detection (F32)
|
100% |
1239
14.7 IPS |
|
|
Face Detection (F16)
|
100% |
1243
14.8 IPS |
|
|
Face Detection (I8)
|
89% |
1111
13.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
7774
60.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
7768
60.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
6245
48.4 IPS |
|
|
Style Transfer (F32)
|
100% |
40366
53.1 IPS |
|
|
Style Transfer (F16)
|
100% |
40290
53.0 IPS |
|
|
Style Transfer (I8)
|
98% |
29898
39.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6613
236.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5757
205.6 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4791
171.1 IPS |
|
|
Text Classification (F32)
|
90% |
675
970.4 IPS |
|
|
Text Classification (F16)
|
90% |
673
967.9 IPS |
|
|
Text Classification (I8)
|
90% |
519
745.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1485
27.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1497
27.5 IPS |
|
|
Machine Translation (I8)
|
70% |
888
16.3 IPS |
