Lenovo ThinkCentre M900 - i5-6500T - Windows 10 LENOVO 10FLS1R000
Geekbench AI Score
1781
Single Precision Score
1779
Half Precision Score
2469
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | paultissue |
| Upload Date | September 08 2025 03:38 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i5-6500T CPU @ 2.50GHz |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | LENOVO 10FLS1R000 |
| Motherboard | LENOVO 30D0 |
| Power Plan | ChrisTitus - Ultimate Power Plan |
| CPU Information | |
|---|---|
| Name | Intel Core i5-6500T |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 94 Stepping 3 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1038
193.0 IPS |
|
|
Image Classification (HP)
|
100% |
1036
192.6 IPS |
|
|
Image Classification (Q)
|
100% |
1561
290.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1133
18.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1150
18.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
1809
29.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2188
2.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
2199
2.57 IPS |
|
|
Pose Estimation (Q)
|
94% |
3939
4.62 IPS |
|
|
Object Detection (SP)
|
100% |
1042
82.7 IPS |
|
|
Object Detection (HP)
|
100% |
1038
82.3 IPS |
|
|
Object Detection (Q)
|
87% |
1635
131.1 IPS |
|
|
Face Detection (SP)
|
100% |
2399
28.5 IPS |
|
|
Face Detection (HP)
|
100% |
2393
28.4 IPS |
|
|
Face Detection (Q)
|
97% |
4180
49.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2767
21.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2758
21.2 IPS |
|
|
Depth Estimation (Q)
|
81% |
4417
34.8 IPS |
|
|
Style Transfer (SP)
|
100% |
6163
7.92 IPS |
|
|
Style Transfer (HP)
|
100% |
6193
7.96 IPS |
|
|
Style Transfer (Q)
|
98% |
11328
14.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1328
49.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1320
48.7 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
2300
85.2 IPS |
|
|
Text Classification (SP)
|
100% |
1271
1.70 KIPS |
|
|
Text Classification (HP)
|
100% |
1263
1.69 KIPS |
|
|
Text Classification (Q)
|
91% |
564
758.6 IPS |
|
|
Machine Translation (SP)
|
100% |
1736
29.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1717
29.6 IPS |
|
|
Machine Translation (Q)
|
100% |
1711
29.5 IPS |
