Dell Inc. Precision M4600
Geekbench AI Score
549
Single Precision Score
567
Half Precision Score
872
Quantized Score
Geekbench AI 1.2.0 for Windows x86 (64-bit)
Result Information
| User | jcpenni |
| Upload Date | December 21 2024 08:18 PM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i7-2860QM CPU @ 2.50GHz |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Dell Inc. Precision M4600 |
| Motherboard | Dell Inc. 08V9YG |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-2860QM |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 42 Stepping 7 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
299
55.7 IPS |
|
|
Image Classification (HP)
|
100% |
330
61.4 IPS |
|
|
Image Classification (Q)
|
100% |
592
110.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
483
7.83 IPS |
|
|
Image Segmentation (HP)
|
100% |
495
8.02 IPS |
|
|
Image Segmentation (Q)
|
99% |
707
11.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
507
0.59 IPS |
|
|
Pose Estimation (HP)
|
100% |
517
0.60 IPS |
|
|
Pose Estimation (Q)
|
94% |
1130
1.33 IPS |
|
|
Object Detection (SP)
|
100% |
294
23.4 IPS |
|
|
Object Detection (HP)
|
100% |
294
23.3 IPS |
|
|
Object Detection (Q)
|
87% |
582
46.6 IPS |
|
|
Face Detection (SP)
|
100% |
996
11.8 IPS |
|
|
Face Detection (HP)
|
100% |
985
11.7 IPS |
|
|
Face Detection (Q)
|
97% |
1695
20.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
958
7.38 IPS |
|
|
Depth Estimation (HP)
|
99% |
949
7.31 IPS |
|
|
Depth Estimation (Q)
|
81% |
1308
10.3 IPS |
|
|
Style Transfer (SP)
|
100% |
1196
1.54 IPS |
|
|
Style Transfer (HP)
|
100% |
1466
1.89 IPS |
|
|
Style Transfer (Q)
|
98% |
3437
4.43 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
441
16.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
435
16.1 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
780
28.9 IPS |
|
|
Text Classification (SP)
|
100% |
448
597.8 IPS |
|
|
Text Classification (HP)
|
100% |
444
592.9 IPS |
|
|
Text Classification (Q)
|
91% |
316
424.1 IPS |
|
|
Machine Translation (SP)
|
100% |
519
8.94 IPS |
|
|
Machine Translation (HP)
|
100% |
528
9.09 IPS |
|
|
Machine Translation (Q)
|
100% |
495
8.53 IPS |
