Main Board MT10
Geekbench AI Score
849
Single Precision Score
784
Half Precision Score
920
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | vincent_wjw |
| Upload Date | July 01 2025 11:11 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i7-4600M CPU @ 2.90GHz |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Main Board MT10 |
| Motherboard | Main Board SM5OPSSB |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i7-4600M |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 60 Stepping 3 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 2 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
509
94.6 IPS |
|
|
Image Classification (HP)
|
100% |
517
96.1 IPS |
|
|
Image Classification (Q)
|
100% |
689
128.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
525
8.52 IPS |
|
|
Image Segmentation (HP)
|
100% |
545
8.83 IPS |
|
|
Image Segmentation (Q)
|
99% |
785
12.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
992
1.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
1005
1.17 IPS |
|
|
Pose Estimation (Q)
|
94% |
1257
1.47 IPS |
|
|
Object Detection (SP)
|
100% |
504
39.9 IPS |
|
|
Object Detection (HP)
|
100% |
514
40.8 IPS |
|
|
Object Detection (Q)
|
87% |
712
57.1 IPS |
|
|
Face Detection (SP)
|
100% |
1084
12.9 IPS |
|
|
Face Detection (HP)
|
100% |
1064
12.6 IPS |
|
|
Face Detection (Q)
|
97% |
1855
22.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1397
10.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
1330
10.2 IPS |
|
|
Depth Estimation (Q)
|
81% |
1649
13.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2961
3.81 IPS |
|
|
Style Transfer (HP)
|
100% |
1816
2.34 IPS |
|
|
Style Transfer (Q)
|
98% |
2868
3.70 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
593
21.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
465
17.2 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
621
23.0 IPS |
|
|
Text Classification (SP)
|
100% |
727
970.9 IPS |
|
|
Text Classification (HP)
|
100% |
702
937.6 IPS |
|
|
Text Classification (Q)
|
91% |
233
313.1 IPS |
|
|
Machine Translation (SP)
|
100% |
755
13.0 IPS |
|
|
Machine Translation (HP)
|
100% |
723
12.5 IPS |
|
|
Machine Translation (Q)
|
100% |
712
12.3 IPS |
