LENOVO 90V6000TUS
Geekbench AI Score
34538
Single Precision Score
50862
Half Precision Score
26516
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | April 17 2025 10:32 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 SUPER |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 90V6000TUS |
| Motherboard | LENOVO 376A |
| Power Plan | Lenovo Default |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900KF |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
13079
2.43 KIPS |
|
|
Image Classification (HP)
|
99% |
18742
3.50 KIPS |
|
|
Image Classification (Q)
|
100% |
11703
2.18 KIPS |
|
|
Image Segmentation (SP)
|
100% |
23338
378.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
30361
492.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
21223
345.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
256841
299.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
495923
578.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
219351
257.0 IPS |
|
|
Object Detection (SP)
|
100% |
17052
1.35 KIPS |
|
|
Object Detection (HP)
|
100% |
23234
1.84 KIPS |
|
|
Object Detection (Q)
|
85% |
14559
1.17 KIPS |
|
|
Face Detection (SP)
|
100% |
47922
569.4 IPS |
|
|
Face Detection (HP)
|
100% |
63744
757.4 IPS |
|
|
Face Detection (Q)
|
97% |
41411
493.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
80529
620.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
152358
1.18 KIPS |
|
|
Depth Estimation (Q)
|
78% |
60410
482.4 IPS |
|
|
Style Transfer (SP)
|
100% |
386125
496.4 IPS |
|
|
Style Transfer (HP)
|
100% |
888733
1.14 KIPS |
|
|
Style Transfer (Q)
|
98% |
345180
445.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
55367
2.04 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
75511
2.79 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
41394
1.53 KIPS |
|
|
Text Classification (SP)
|
100% |
3849
5.14 KIPS |
|
|
Text Classification (HP)
|
99% |
4849
6.47 KIPS |
|
|
Text Classification (Q)
|
97% |
2260
3.03 KIPS |
|
|
Machine Translation (SP)
|
100% |
5690
98.0 IPS |
|
|
Machine Translation (HP)
|
100% |
5592
96.3 IPS |
|
|
Machine Translation (Q)
|
70% |
2682
50.3 IPS |
