LENOVO 83BF
Geekbench AI Score
65
Single Precision Score
65
Half Precision Score
49
Quantized Score
Geekbench AI 1.5.0 for Linux x86 (64-bit)
Result Information
| User | dmitrychou |
| Upload Date | October 05 2025 07:57 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Core i5-12450H |
| System Information | |
|---|---|
| Operating System | Linux Mint 22.2 |
| Model | LENOVO 83BF |
| Motherboard | LENOVO LNVNB161216 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-12450H |
| Topology | 1 Processor, 8 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 154 Stepping 3 |
| Base Frequency | 4.40 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.35 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
39
7.26 IPS |
|
|
Image Classification (HP)
|
100% |
37
6.81 IPS |
|
|
Image Classification (Q)
|
97% |
30
5.53 IPS |
|
|
Image Segmentation (SP)
|
100% |
50
0.82 IPS |
|
|
Image Segmentation (HP)
|
100% |
50
0.81 IPS |
|
|
Image Segmentation (Q)
|
98% |
39
0.64 IPS |
|
|
Pose Estimation (SP)
|
100% |
59
0.07 IPS |
|
|
Pose Estimation (HP)
|
100% |
59
0.07 IPS |
|
|
Pose Estimation (Q)
|
96% |
50
0.06 IPS |
|
|
Object Detection (SP)
|
100% |
36
2.87 IPS |
|
|
Object Detection (HP)
|
100% |
36
2.88 IPS |
|
|
Object Detection (Q)
|
87% |
29
2.33 IPS |
|
|
Face Detection (SP)
|
100% |
119
1.42 IPS |
|
|
Face Detection (HP)
|
100% |
120
1.42 IPS |
|
|
Face Detection (Q)
|
97% |
95
1.13 IPS |
|
|
Depth Estimation (SP)
|
100% |
87
0.67 IPS |
|
|
Depth Estimation (HP)
|
99% |
86
0.66 IPS |
|
|
Depth Estimation (Q)
|
64% |
60
0.55 IPS |
|
|
Style Transfer (SP)
|
100% |
183
0.23 IPS |
|
|
Style Transfer (HP)
|
100% |
183
0.23 IPS |
|
|
Style Transfer (Q)
|
98% |
155
0.20 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
40
1.49 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
40
1.48 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
32
1.20 IPS |
|
|
Text Classification (SP)
|
100% |
54
72.1 IPS |
|
|
Text Classification (HP)
|
100% |
54
72.0 IPS |
|
|
Text Classification (Q)
|
91% |
37
49.4 IPS |
|
|
Machine Translation (SP)
|
100% |
92
1.58 IPS |
|
|
Machine Translation (HP)
|
100% |
91
1.57 IPS |
|
|
Machine Translation (Q)
|
58% |
48
1.14 IPS |
