LENOVO 90YA0012US
Geekbench AI Score
28744
Single Precision Score
50910
Half Precision Score
22003
Quantized Score
Geekbench AI 1.4.0 Corporate for Windows AVX2
Result Information
| Upload Date | June 25 2025 12:46 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 90YA0012US |
| Motherboard | LENOVO 378B |
| Power Plan | Lenovo Default |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 265KF |
| Topology | 1 Processor, 20 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11343
2.11 KIPS |
|
|
Image Classification (HP)
|
100% |
19778
3.68 KIPS |
|
|
Image Classification (Q)
|
100% |
10121
1.88 KIPS |
|
|
Image Segmentation (SP)
|
100% |
21904
355.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
33702
546.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
19706
320.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
165451
193.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
465628
543.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
139999
164.0 IPS |
|
|
Object Detection (SP)
|
100% |
15093
1.20 KIPS |
|
|
Object Detection (HP)
|
100% |
26017
2.06 KIPS |
|
|
Object Detection (Q)
|
83% |
12572
1.02 KIPS |
|
|
Face Detection (SP)
|
100% |
40726
483.9 IPS |
|
|
Face Detection (HP)
|
100% |
62110
738.0 IPS |
|
|
Face Detection (Q)
|
97% |
34225
408.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
67580
520.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
129004
993.9 IPS |
|
|
Depth Estimation (Q)
|
78% |
52525
419.2 IPS |
|
|
Style Transfer (SP)
|
100% |
224615
288.7 IPS |
|
|
Style Transfer (HP)
|
100% |
773036
993.7 IPS |
|
|
Style Transfer (Q)
|
98% |
197056
254.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
40537
1.50 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
75735
2.80 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
32647
1.21 KIPS |
|
|
Text Classification (SP)
|
100% |
3895
5.20 KIPS |
|
|
Text Classification (HP)
|
100% |
4838
6.46 KIPS |
|
|
Text Classification (Q)
|
97% |
2314
3.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
6358
109.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6383
110.0 IPS |
|
|
Machine Translation (Q)
|
70% |
2832
53.1 IPS |
