Dynabook Inc. PORTEGE Z40L-N
Geekbench AI Score
18706
Single Precision Score
18324
Half Precision Score
25581
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| Upload Date | September 14 2024 03:16 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| 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% |
12223
2.27 KIPS |
|
|
Image Classification (HP)
|
100% |
12258
2.28 KIPS |
|
|
Image Classification (Q)
|
100% |
17305
3.22 KIPS |
|
|
Image Segmentation (SP)
|
100% |
4964
80.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
4918
79.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
7321
118.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
100484
117.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
100930
117.8 IPS |
|
|
Pose Estimation (Q)
|
96% |
188796
221.2 IPS |
|
|
Object Detection (SP)
|
98% |
14103
1.12 KIPS |
|
|
Object Detection (HP)
|
100% |
14061
1.12 KIPS |
|
|
Object Detection (Q)
|
87% |
18472
1.48 KIPS |
|
|
Face Detection (SP)
|
100% |
24374
289.6 IPS |
|
|
Face Detection (HP)
|
100% |
24384
289.7 IPS |
|
|
Face Detection (Q)
|
100% |
45383
539.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
66451
512.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
56568
435.8 IPS |
|
|
Depth Estimation (Q)
|
80% |
100092
792.9 IPS |
|
|
Style Transfer (SP)
|
100% |
214647
275.9 IPS |
|
|
Style Transfer (HP)
|
100% |
194074
249.5 IPS |
|
|
Style Transfer (Q)
|
98% |
295638
381.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
31609
1.17 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
31508
1.16 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
48852
1.81 KIPS |
|
|
Text Classification (SP)
|
100% |
2283
3.05 KIPS |
|
|
Text Classification (HP)
|
100% |
2461
3.28 KIPS |
|
|
Text Classification (Q)
|
92% |
2100
2.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
2432
41.9 IPS |
|
|
Machine Translation (HP)
|
100% |
2404
41.4 IPS |
|
|
Machine Translation (Q)
|
89% |
1972
34.3 IPS |
