Dynabook Inc. PORTEGE Z40L-N
Geekbench AI Score
2595
Single Precision Score
24462
Half Precision Score
35445
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | June 18 2025 06:08 AM |
| Views | 3 |
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. OK0129/0000 |
| Power Plan | dynabook standard |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 258V |
| 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 | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1862
346.3 IPS |
|
|
Image Classification (HP)
|
100% |
13034
2.42 KIPS |
|
|
Image Classification (Q)
|
100% |
18969
3.53 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2113
34.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
18479
299.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
28051
454.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2566
2.99 IPS |
|
|
Pose Estimation (HP)
|
100% |
109284
127.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
216657
253.8 IPS |
|
|
Object Detection (SP)
|
100% |
1363
108.1 IPS |
|
|
Object Detection (HP)
|
100% |
16480
1.31 KIPS |
|
|
Object Detection (Q)
|
87% |
24142
1.94 KIPS |
|
|
Face Detection (SP)
|
100% |
4132
49.1 IPS |
|
|
Face Detection (HP)
|
100% |
38382
456.1 IPS |
|
|
Face Detection (Q)
|
100% |
58778
698.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
3440
26.5 IPS |
|
|
Depth Estimation (HP)
|
93% |
71982
557.6 IPS |
|
|
Depth Estimation (Q)
|
88% |
141599
1.10 KIPS |
|
|
Style Transfer (SP)
|
100% |
7149
9.19 IPS |
|
|
Style Transfer (HP)
|
100% |
208518
268.1 IPS |
|
|
Style Transfer (Q)
|
98% |
335352
432.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1553
57.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
27747
1.02 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
42085
1.56 KIPS |
|
|
Text Classification (SP)
|
100% |
2028
2.71 KIPS |
|
|
Text Classification (HP)
|
100% |
2655
3.54 KIPS |
|
|
Text Classification (Q)
|
92% |
2315
3.11 KIPS |
|
|
Machine Translation (SP)
|
100% |
3154
54.3 IPS |
|
|
Machine Translation (HP)
|
100% |
4169
71.8 IPS |
|
|
Machine Translation (Q)
|
100% |
4136
71.3 IPS |
