LENOVO 83F5
Geekbench AI Score
34339
Single Precision Score
58763
Half Precision Score
26590
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | 1ikhan |
| Upload Date | August 27 2025 02:44 AM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5090 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 83F5 |
| Motherboard | LENOVO LNVNB161216 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 275HX |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
13718
2.55 KIPS |
|
|
Image Classification (HP)
|
100% |
21131
3.93 KIPS |
|
|
Image Classification (Q)
|
100% |
12099
2.25 KIPS |
|
|
Image Segmentation (SP)
|
100% |
26503
429.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
37835
613.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
23668
384.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
217521
253.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
654084
763.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
184130
215.7 IPS |
|
|
Object Detection (SP)
|
100% |
17020
1.35 KIPS |
|
|
Object Detection (HP)
|
100% |
25336
2.01 KIPS |
|
|
Object Detection (Q)
|
86% |
15285
1.23 KIPS |
|
|
Face Detection (SP)
|
100% |
51008
606.1 IPS |
|
|
Face Detection (HP)
|
100% |
75699
899.5 IPS |
|
|
Face Detection (Q)
|
97% |
42576
507.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
83472
643.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
167929
1.29 KIPS |
|
|
Depth Estimation (Q)
|
78% |
63632
508.1 IPS |
|
|
Style Transfer (SP)
|
100% |
308705
396.8 IPS |
|
|
Style Transfer (HP)
|
100% |
1021414
1.31 KIPS |
|
|
Style Transfer (Q)
|
98% |
271999
350.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
48567
1.79 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
81532
3.01 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
38464
1.42 KIPS |
|
|
Text Classification (SP)
|
100% |
3854
5.14 KIPS |
|
|
Text Classification (HP)
|
100% |
5018
6.70 KIPS |
|
|
Text Classification (Q)
|
97% |
2498
3.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
6885
118.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6976
120.2 IPS |
|
|
Machine Translation (Q)
|
70% |
3097
58.1 IPS |
