TOSHIBA EQUIUM 4070
Geekbench AI Score
1529
Single Precision Score
1506
Half Precision Score
2748
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | jcpenni |
| Upload Date | December 21 2024 03:53 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i5-6500 CPU @ 3.20GHz |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | TOSHIBA EQUIUM 4070 |
| Motherboard | TOSHIBA MDB15TV-TJ |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-6500 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 94 Stepping 3 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 4.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1004
186.7 IPS |
|
|
Image Classification (HP)
|
100% |
1007
187.2 IPS |
|
|
Image Classification (Q)
|
100% |
1834
341.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
704
11.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
715
11.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
1656
26.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2374
2.77 IPS |
|
|
Pose Estimation (HP)
|
100% |
2354
2.75 IPS |
|
|
Pose Estimation (Q)
|
94% |
4720
5.54 IPS |
|
|
Object Detection (SP)
|
100% |
866
68.7 IPS |
|
|
Object Detection (HP)
|
100% |
882
70.0 IPS |
|
|
Object Detection (Q)
|
87% |
1825
146.4 IPS |
|
|
Face Detection (SP)
|
100% |
1230
14.6 IPS |
|
|
Face Detection (HP)
|
100% |
1229
14.6 IPS |
|
|
Face Detection (Q)
|
97% |
4203
50.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
2621
20.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
2618
20.2 IPS |
|
|
Depth Estimation (Q)
|
81% |
5103
40.3 IPS |
|
|
Style Transfer (SP)
|
100% |
6535
8.40 IPS |
|
|
Style Transfer (HP)
|
100% |
6582
8.46 IPS |
|
|
Style Transfer (Q)
|
98% |
13273
17.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1326
48.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1299
48.0 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
2728
101.1 IPS |
|
|
Text Classification (SP)
|
100% |
1631
2.18 KIPS |
|
|
Text Classification (HP)
|
100% |
1605
2.14 KIPS |
|
|
Text Classification (Q)
|
91% |
1144
1.54 KIPS |
|
|
Machine Translation (SP)
|
100% |
1061
18.3 IPS |
|
|
Machine Translation (HP)
|
100% |
912
15.7 IPS |
|
|
Machine Translation (Q)
|
100% |
1059
18.3 IPS |
