Dynabook Inc. PORTEGE Z40L-N
Geekbench AI Score
7464
Single Precision Score
12813
Half Precision Score
4872
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| Upload Date | September 14 2024 01:48 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Arc(TM) 140V GPU (8GB) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Dynabook Inc. PORTEGE Z40L-N |
| Motherboard | Dynabook Inc. OK0125/0000 |
| Power Plan | dynabook standard |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 266V |
| Topology | 1 Processor, 8 Cores |
| Identifier | GenuineIntel Family 6 Model 189 Stepping 1 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4361
811.0 IPS |
|
|
Image Classification (HP)
|
100% |
5800
1.08 KIPS |
|
|
Image Classification (Q)
|
100% |
3177
590.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
6704
108.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
12398
201.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4874
79.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
22460
26.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
92248
107.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
18123
21.2 IPS |
|
|
Object Detection (SP)
|
100% |
4762
377.8 IPS |
|
|
Object Detection (HP)
|
100% |
7467
592.3 IPS |
|
|
Object Detection (Q)
|
89% |
3771
301.7 IPS |
|
|
Face Detection (SP)
|
100% |
7394
87.9 IPS |
|
|
Face Detection (HP)
|
100% |
13657
162.3 IPS |
|
|
Face Detection (Q)
|
97% |
5483
65.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
19140
147.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
40092
308.9 IPS |
|
|
Depth Estimation (Q)
|
74% |
12359
100.7 IPS |
|
|
Style Transfer (SP)
|
100% |
56617
72.8 IPS |
|
|
Style Transfer (HP)
|
100% |
131350
168.9 IPS |
|
|
Style Transfer (Q)
|
98% |
45395
58.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9919
366.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
14361
530.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5191
192.2 IPS |
|
|
Text Classification (SP)
|
100% |
1247
1.66 KIPS |
|
|
Text Classification (HP)
|
100% |
1467
1.96 KIPS |
|
|
Text Classification (Q)
|
97% |
641
857.9 IPS |
|
|
Machine Translation (SP)
|
100% |
1732
29.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1590
27.4 IPS |
|
|
Machine Translation (Q)
|
60% |
697
15.6 IPS |
