NEC PC-MK28ELZDUBSN
Geekbench AI Score
852
Single Precision Score
848
Half Precision Score
621
Quantized Score
Geekbench AI 1.4.0 for Linux AVX2
Result Information
| User | hisyho |
| Upload Date | September 03 2025 04:58 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Core i7-4790 |
| System Information | |
|---|---|
| Operating System | Ubuntu 24.04.3 LTS |
| Model | NEC PC-MK28ELZDUBSN |
| Motherboard | NEC 3098 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-4790 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 60 Stepping 3 |
| Base Frequency | 4.00 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 14.58 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
656
122.0 IPS |
|
|
Image Classification (HP)
|
100% |
648
120.5 IPS |
|
|
Image Classification (Q)
|
99% |
412
76.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
732
11.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
722
11.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
454
7.38 IPS |
|
|
Pose Estimation (SP)
|
100% |
1015
1.18 IPS |
|
|
Pose Estimation (HP)
|
100% |
1016
1.19 IPS |
|
|
Pose Estimation (Q)
|
96% |
1058
1.24 IPS |
|
|
Object Detection (SP)
|
100% |
662
52.5 IPS |
|
|
Object Detection (HP)
|
100% |
670
53.1 IPS |
|
|
Object Detection (Q)
|
85% |
451
36.3 IPS |
|
|
Face Detection (SP)
|
100% |
973
11.6 IPS |
|
|
Face Detection (HP)
|
100% |
931
11.1 IPS |
|
|
Face Detection (Q)
|
97% |
965
11.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
964
7.43 IPS |
|
|
Depth Estimation (HP)
|
99% |
968
7.46 IPS |
|
|
Depth Estimation (Q)
|
63% |
838
7.86 IPS |
|
|
Style Transfer (SP)
|
100% |
1278
1.64 IPS |
|
|
Style Transfer (HP)
|
100% |
1274
1.64 IPS |
|
|
Style Transfer (Q)
|
98% |
2084
2.69 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
562
20.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
567
20.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
581
21.5 IPS |
|
|
Text Classification (SP)
|
100% |
955
1.27 KIPS |
|
|
Text Classification (HP)
|
100% |
966
1.29 KIPS |
|
|
Text Classification (Q)
|
92% |
325
436.1 IPS |
|
|
Machine Translation (SP)
|
100% |
975
16.8 IPS |
|
|
Machine Translation (HP)
|
100% |
961
16.5 IPS |
|
|
Machine Translation (Q)
|
58% |
301
7.06 IPS |
