LENOVO 20EQS12Q02
Geekbench AI Score
1916
Single Precision Score
1935
Half Precision Score
2926
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| User | somata |
| Upload Date | August 18 2024 01:56 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i7-6820HQ CPU @ 2.70GHz |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | LENOVO 20EQS12Q02 |
| Motherboard | LENOVO 20EQS12Q02 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-6820HQ |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 94 Stepping 3 |
| Base Frequency | 2.71 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1151
214.1 IPS |
|
|
Image Classification (HP)
|
100% |
1224
227.6 IPS |
|
|
Image Classification (Q)
|
100% |
1757
326.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1079
17.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1076
17.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
1905
31.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2394
2.79 IPS |
|
|
Pose Estimation (HP)
|
100% |
2445
2.85 IPS |
|
|
Pose Estimation (Q)
|
94% |
4449
5.22 IPS |
|
|
Object Detection (SP)
|
100% |
1179
93.5 IPS |
|
|
Object Detection (HP)
|
100% |
1204
95.5 IPS |
|
|
Object Detection (Q)
|
87% |
1936
155.2 IPS |
|
|
Face Detection (SP)
|
100% |
2335
27.7 IPS |
|
|
Face Detection (HP)
|
100% |
2253
26.8 IPS |
|
|
Face Detection (Q)
|
97% |
4861
58.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
3209
24.7 IPS |
|
|
Depth Estimation (HP)
|
100% |
3209
24.7 IPS |
|
|
Depth Estimation (Q)
|
79% |
5081
40.3 IPS |
|
|
Style Transfer (SP)
|
100% |
7013
9.01 IPS |
|
|
Style Transfer (HP)
|
100% |
7057
9.07 IPS |
|
|
Style Transfer (Q)
|
98% |
12759
16.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1392
51.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1402
51.8 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
2656
98.4 IPS |
|
|
Text Classification (SP)
|
100% |
1296
1.73 KIPS |
|
|
Text Classification (HP)
|
100% |
1284
1.71 KIPS |
|
|
Text Classification (Q)
|
91% |
1056
1.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
2008
34.6 IPS |
|
|
Machine Translation (HP)
|
100% |
2071
35.7 IPS |
|
|
Machine Translation (Q)
|
90% |
1810
31.4 IPS |
