LENOVO 83F5
Geekbench ML Score
20184
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | November 23 2025 02:46 PM |
| Views | 14 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | LENOVO 83F5 |
| Motherboard | LENOVO LNVNB161216 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core 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 |
| L1 Instruction Cache | 64.0 KB x 12 |
| L1 Data Cache | 48.0 KB x 12 |
| L2 Cache | 3.00 MB x 3 |
| L3 Cache | 36.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 Ti Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
9967
1.87 KIPS |
|
|
Image Classification (F16)
|
100% |
9186
1.72 KIPS |
|
|
Image Classification (I8)
|
100% |
8324
1.56 KIPS |
|
|
Image Segmentation (F32)
|
100% |
16518
275.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
16125
269.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
14363
239.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
117447
142.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
117347
142.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
116139
140.6 IPS |
|
|
Object Detection (F32)
|
100% |
7478
558.3 IPS |
|
|
Object Detection (F16)
|
100% |
7545
563.3 IPS |
|
|
Object Detection (I8)
|
57% |
6936
517.8 IPS |
|
|
Face Detection (F32)
|
100% |
29755
353.8 IPS |
|
|
Face Detection (F16)
|
100% |
29758
353.8 IPS |
|
|
Face Detection (I8)
|
89% |
24871
295.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
58436
453.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
57859
448.7 IPS |
|
|
Depth Estimation (I8)
|
94% |
47766
370.4 IPS |
|
|
Style Transfer (F32)
|
100% |
196681
258.7 IPS |
|
|
Style Transfer (F16)
|
100% |
196720
258.8 IPS |
|
|
Style Transfer (I8)
|
98% |
167620
220.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
34147
1.22 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
34605
1.24 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
26515
946.9 IPS |
|
|
Text Classification (F32)
|
100% |
3403
4.89 KIPS |
|
|
Text Classification (F16)
|
100% |
3029
4.35 KIPS |
|
|
Text Classification (I8)
|
98% |
2103
3.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
4648
85.5 IPS |
|
|
Machine Translation (F16)
|
100% |
4648
85.5 IPS |
|
|
Machine Translation (I8)
|
70% |
2289
42.1 IPS |
