LENOVO 90V7003NUS
Geekbench AI Score
34948
Single Precision Score
50985
Half Precision Score
27030
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | 1BadVan |
| Upload Date | June 12 2025 04:29 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | LENOVO 90V7003NUS |
| Motherboard | LENOVO 376A |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i7-13700KF |
| Topology | 1 Processor, 16 Cores, 24 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
13339
2.48 KIPS |
|
|
Image Classification (HP)
|
99% |
18712
3.49 KIPS |
|
|
Image Classification (Q)
|
100% |
11476
2.13 KIPS |
|
|
Image Segmentation (SP)
|
100% |
23766
385.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
30614
496.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
21583
351.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
260304
303.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
517315
603.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
232112
272.0 IPS |
|
|
Object Detection (SP)
|
100% |
16725
1.33 KIPS |
|
|
Object Detection (HP)
|
100% |
23428
1.86 KIPS |
|
|
Object Detection (Q)
|
85% |
14417
1.16 KIPS |
|
|
Face Detection (SP)
|
100% |
49009
582.3 IPS |
|
|
Face Detection (HP)
|
100% |
64180
762.6 IPS |
|
|
Face Detection (Q)
|
97% |
41586
495.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
83507
643.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
153129
1.18 KIPS |
|
|
Depth Estimation (Q)
|
78% |
64149
512.3 IPS |
|
|
Style Transfer (SP)
|
100% |
394310
506.9 IPS |
|
|
Style Transfer (HP)
|
100% |
867948
1.12 KIPS |
|
|
Style Transfer (Q)
|
98% |
346736
447.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
54865
2.03 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
74464
2.75 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
42228
1.56 KIPS |
|
|
Text Classification (SP)
|
100% |
3697
4.93 KIPS |
|
|
Text Classification (HP)
|
99% |
4556
6.08 KIPS |
|
|
Text Classification (Q)
|
97% |
2268
3.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
6017
103.6 IPS |
|
|
Machine Translation (HP)
|
100% |
5908
101.8 IPS |
|
|
Machine Translation (Q)
|
70% |
2836
53.2 IPS |
