LENOVO 82RF
Geekbench AI Score
16489
Single Precision Score
26528
Half Precision Score
10592
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | hooverbw |
| Upload Date | October 13 2025 09:40 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 3070 Ti Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Enterprise (64-bit) |
| Model | LENOVO 82RF |
| Motherboard | LENOVO LNVNB161216 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-12700H |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 154 Stepping 3 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6600
1.23 KIPS |
|
|
Image Classification (HP)
|
99% |
10456
1.95 KIPS |
|
|
Image Classification (Q)
|
100% |
4710
875.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
11294
183.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
16504
267.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
9023
146.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
84103
98.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
254974
297.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
69588
81.5 IPS |
|
|
Object Detection (SP)
|
100% |
8148
646.3 IPS |
|
|
Object Detection (HP)
|
100% |
12331
978.1 IPS |
|
|
Object Detection (Q)
|
85% |
6280
505.6 IPS |
|
|
Face Detection (SP)
|
100% |
21218
252.1 IPS |
|
|
Face Detection (HP)
|
100% |
32395
384.9 IPS |
|
|
Face Detection (Q)
|
97% |
15896
189.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
36830
283.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
75765
583.7 IPS |
|
|
Depth Estimation (Q)
|
77% |
26392
211.0 IPS |
|
|
Style Transfer (SP)
|
100% |
156612
201.3 IPS |
|
|
Style Transfer (HP)
|
100% |
389760
501.0 IPS |
|
|
Style Transfer (Q)
|
98% |
118678
153.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
27659
1.02 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
36897
1.36 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
15315
567.1 IPS |
|
|
Text Classification (SP)
|
100% |
2709
3.62 KIPS |
|
|
Text Classification (HP)
|
100% |
3123
4.17 KIPS |
|
|
Text Classification (Q)
|
97% |
1132
1.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
3172
54.6 IPS |
|
|
Machine Translation (HP)
|
100% |
2886
49.7 IPS |
|
|
Machine Translation (Q)
|
70% |
1109
20.8 IPS |
