LENOVO 10S0S0S900
Geekbench AI Score
232
Single Precision Score
229
Half Precision Score
205
Quantized Score
Geekbench AI 1.4.0 for Linux AVX2
Result Information
| Upload Date | August 28 2025 06:56 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Core i7-9700T |
| System Information | |
|---|---|
| Operating System | Debian GNU/Linux 13 (trixie) |
| Model | LENOVO 10S0S0S900 |
| Motherboard | LENOVO 3135 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-9700T |
| Topology | 1 Processor, 8 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 13 |
| Base Frequency | 4.30 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 62.64 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
77
14.4 IPS |
|
|
Image Classification (HP)
|
100% |
86
16.0 IPS |
|
|
Image Classification (Q)
|
99% |
75
14.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
355
5.76 IPS |
|
|
Image Segmentation (HP)
|
100% |
355
5.75 IPS |
|
|
Image Segmentation (Q)
|
98% |
275
4.46 IPS |
|
|
Pose Estimation (SP)
|
100% |
1353
1.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
1355
1.58 IPS |
|
|
Pose Estimation (Q)
|
96% |
1320
1.55 IPS |
|
|
Object Detection (SP)
|
100% |
124
9.81 IPS |
|
|
Object Detection (HP)
|
100% |
135
10.7 IPS |
|
|
Object Detection (Q)
|
85% |
117
9.41 IPS |
|
|
Face Detection (SP)
|
100% |
410
4.87 IPS |
|
|
Face Detection (HP)
|
100% |
427
5.08 IPS |
|
|
Face Detection (Q)
|
97% |
380
4.53 IPS |
|
|
Depth Estimation (SP)
|
100% |
447
3.44 IPS |
|
|
Depth Estimation (HP)
|
99% |
447
3.44 IPS |
|
|
Depth Estimation (Q)
|
63% |
341
3.20 IPS |
|
|
Style Transfer (SP)
|
100% |
1866
2.40 IPS |
|
|
Style Transfer (HP)
|
100% |
1877
2.41 IPS |
|
|
Style Transfer (Q)
|
98% |
2615
3.37 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
253
9.33 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
247
9.12 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
242
8.98 IPS |
|
|
Text Classification (SP)
|
100% |
24
32.2 IPS |
|
|
Text Classification (HP)
|
100% |
17
23.1 IPS |
|
|
Text Classification (Q)
|
92% |
18
24.4 IPS |
|
|
Machine Translation (SP)
|
100% |
48
0.83 IPS |
|
|
Machine Translation (HP)
|
100% |
48
0.83 IPS |
|
|
Machine Translation (Q)
|
58% |
29
0.69 IPS |
