LENOVO MT-M 10TV-CT01WW
Geekbench AI Score
2714
Single Precision Score
1144
Half Precision Score
3974
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | September 12 2025 09:18 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i7-9700 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO MT-M 10TV-CT01WW |
| Motherboard | LENOVO 313A |
| CPU Information | |
|---|---|
| Name | Intel Core i7-9700 |
| Topology | 1 Processor, 8 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 13 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2362
439.3 IPS |
|
|
Image Classification (HP)
|
100% |
353
65.7 IPS |
|
|
Image Classification (Q)
|
96% |
3346
624.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
870
14.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
650
10.5 IPS |
|
|
Image Segmentation (Q)
|
97% |
4410
71.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
4709
5.49 IPS |
|
|
Pose Estimation (HP)
|
100% |
3499
4.08 IPS |
|
|
Pose Estimation (Q)
|
86% |
7858
9.29 IPS |
|
|
Object Detection (SP)
|
100% |
2286
181.4 IPS |
|
|
Object Detection (HP)
|
100% |
476
37.7 IPS |
|
|
Object Detection (Q)
|
58% |
2412
263.6 IPS |
|
|
Face Detection (SP)
|
100% |
2995
35.6 IPS |
|
|
Face Detection (HP)
|
100% |
982
11.7 IPS |
|
|
Face Detection (Q)
|
96% |
5887
70.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6521
50.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
1510
11.6 IPS |
|
|
Depth Estimation (Q)
|
78% |
7951
63.4 IPS |
|
|
Style Transfer (SP)
|
100% |
11413
14.7 IPS |
|
|
Style Transfer (HP)
|
100% |
9147
11.8 IPS |
|
|
Style Transfer (Q)
|
87% |
12126
15.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2060
76.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1795
66.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3308
122.6 IPS |
|
|
Text Classification (SP)
|
100% |
1355
1.81 KIPS |
|
|
Text Classification (HP)
|
100% |
668
892.3 IPS |
|
|
Text Classification (Q)
|
97% |
1048
1.40 KIPS |
|
|
Machine Translation (SP)
|
100% |
1578
27.2 IPS |
|
|
Machine Translation (HP)
|
100% |
619
10.7 IPS |
|
|
Machine Translation (Q)
|
68% |
1788
34.5 IPS |
