Dynabook Inc. PORTEGE Z40L-N
Geekbench AI Score
17810
Single Precision Score
18194
Half Precision Score
26055
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| Upload Date | September 14 2024 03:19 AM |
| Views | 5 |
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% |
11194
2.08 KIPS |
|
|
Image Classification (HP)
|
100% |
11749
2.18 KIPS |
|
|
Image Classification (Q)
|
100% |
17955
3.34 KIPS |
|
|
Image Segmentation (SP)
|
100% |
4846
78.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
5047
81.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
7282
118.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
98903
115.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
98273
114.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
187020
219.1 IPS |
|
|
Object Detection (SP)
|
98% |
14087
1.12 KIPS |
|
|
Object Detection (HP)
|
100% |
14464
1.15 KIPS |
|
|
Object Detection (Q)
|
87% |
19021
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
24128
286.7 IPS |
|
|
Face Detection (HP)
|
100% |
24292
288.6 IPS |
|
|
Face Detection (Q)
|
100% |
45945
545.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
65165
502.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
58880
453.6 IPS |
|
|
Depth Estimation (Q)
|
80% |
102166
809.4 IPS |
|
|
Style Transfer (SP)
|
100% |
202740
260.6 IPS |
|
|
Style Transfer (HP)
|
100% |
207513
266.8 IPS |
|
|
Style Transfer (Q)
|
98% |
302882
390.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
23965
884.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32374
1.20 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
47982
1.78 KIPS |
|
|
Text Classification (SP)
|
100% |
2416
3.22 KIPS |
|
|
Text Classification (HP)
|
100% |
2057
2.75 KIPS |
|
|
Text Classification (Q)
|
92% |
2278
3.06 KIPS |
|
|
Machine Translation (SP)
|
100% |
2302
39.6 IPS |
|
|
Machine Translation (HP)
|
100% |
2387
41.1 IPS |
|
|
Machine Translation (Q)
|
89% |
1995
34.7 IPS |
