ALLDOCUBE i1115D
Geekbench AI Score
2027
Single Precision Score
3284
Half Precision Score
4889
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | KD8UXA |
| Upload Date | December 28 2024 12:08 AM |
| Views | 15 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Iris(R) Xe Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | ALLDOCUBE i1115D |
| Motherboard | ALLDOCUBE ALLDOCUBE |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-1135G7 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 140 Stepping 1 |
| Base Frequency | 2.42 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1356
252.1 IPS |
|
|
Image Classification (HP)
|
100% |
2513
467.3 IPS |
|
|
Image Classification (Q)
|
99% |
2977
555.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1475
23.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
3138
50.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
4550
73.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
2626
3.06 IPS |
|
|
Pose Estimation (HP)
|
99% |
3368
3.93 IPS |
|
|
Pose Estimation (Q)
|
97% |
14141
16.6 IPS |
|
|
Object Detection (SP)
|
100% |
1232
97.7 IPS |
|
|
Object Detection (HP)
|
100% |
1950
154.7 IPS |
|
|
Object Detection (Q)
|
90% |
2937
234.8 IPS |
|
|
Face Detection (SP)
|
100% |
3925
46.6 IPS |
|
|
Face Detection (HP)
|
100% |
6197
73.6 IPS |
|
|
Face Detection (Q)
|
100% |
9213
109.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
4235
32.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
8629
66.7 IPS |
|
|
Depth Estimation (Q)
|
89% |
10259
79.8 IPS |
|
|
Style Transfer (SP)
|
100% |
10585
13.6 IPS |
|
|
Style Transfer (HP)
|
100% |
23162
29.8 IPS |
|
|
Style Transfer (Q)
|
98% |
43877
56.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2321
85.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3564
131.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5421
200.8 IPS |
|
|
Text Classification (SP)
|
71% |
657
950.9 IPS |
|
|
Text Classification (HP)
|
71% |
746
1.08 KIPS |
|
|
Text Classification (Q)
|
92% |
712
956.4 IPS |
|
|
Machine Translation (SP)
|
100% |
675
11.6 IPS |
|
|
Machine Translation (HP)
|
100% |
857
14.8 IPS |
|
|
Machine Translation (Q)
|
100% |
867
14.9 IPS |
