LENOVO 1607S8T
Geekbench AI Score
3636
Single Precision Score
3658
Half Precision Score
2798
Quantized Score
Geekbench AI 1.3.0 for Windows x86 (64-bit)
Result Information
| User | paisarn |
| Upload Date | November 22 2025 04:01 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce GTX 1050 Ti |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | LENOVO 1607S8T |
| Motherboard | LENOVO To be filled by O.E.M. |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i5-2400 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 42 Stepping 7 |
| Base Frequency | 3.10 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
821
152.7 IPS |
|
|
Image Classification (HP)
|
100% |
1523
283.2 IPS |
|
|
Image Classification (Q)
|
100% |
766
142.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2342
38.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2112
34.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1957
31.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
20291
23.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
11036
12.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
16957
19.9 IPS |
|
|
Object Detection (SP)
|
100% |
1163
92.2 IPS |
|
|
Object Detection (HP)
|
100% |
1894
150.2 IPS |
|
|
Object Detection (Q)
|
83% |
1051
84.9 IPS |
|
|
Face Detection (SP)
|
100% |
2300
27.3 IPS |
|
|
Face Detection (HP)
|
100% |
3441
40.9 IPS |
|
|
Face Detection (Q)
|
97% |
2059
24.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7626
58.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
6879
53.1 IPS |
|
|
Depth Estimation (Q)
|
77% |
6214
49.7 IPS |
|
|
Style Transfer (SP)
|
100% |
33626
43.2 IPS |
|
|
Style Transfer (HP)
|
100% |
20554
26.4 IPS |
|
|
Style Transfer (Q)
|
98% |
27781
35.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7106
262.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5298
195.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4858
179.9 IPS |
|
|
Text Classification (SP)
|
100% |
1140
1.52 KIPS |
|
|
Text Classification (HP)
|
100% |
1366
1.82 KIPS |
|
|
Text Classification (Q)
|
97% |
712
953.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1865
32.1 IPS |
|
|
Machine Translation (HP)
|
96% |
1817
31.4 IPS |
|
|
Machine Translation (Q)
|
70% |
897
16.8 IPS |
