DERE v9max intel
Geekbench AI Score
3128
Single Precision Score
3925
Half Precision Score
8010
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | luchnik |
| Upload Date | October 19 2025 10:13 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Iris(R) Xe Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Windows 10 Pro (64-bit) |
| Model | intel |
| Motherboard | |
| CPU Information | |
|---|---|
| Name | Intel Core i7-1165G7 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 140 Stepping 1 |
| Base Frequency | 2.80 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1827
339.7 IPS |
|
|
Image Classification (HP)
|
100% |
3356
624.0 IPS |
|
|
Image Classification (Q)
|
99% |
5641
1.05 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2430
39.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
4797
77.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
6061
98.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
8210
9.58 IPS |
|
|
Pose Estimation (HP)
|
99% |
6569
7.66 IPS |
|
|
Pose Estimation (Q)
|
97% |
26695
31.3 IPS |
|
|
Object Detection (SP)
|
100% |
1958
155.3 IPS |
|
|
Object Detection (HP)
|
100% |
3036
240.9 IPS |
|
|
Object Detection (Q)
|
90% |
5161
412.7 IPS |
|
|
Face Detection (SP)
|
100% |
2885
34.3 IPS |
|
|
Face Detection (HP)
|
100% |
6405
76.1 IPS |
|
|
Face Detection (Q)
|
100% |
11529
137.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6724
51.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
11648
90.0 IPS |
|
|
Depth Estimation (Q)
|
89% |
16510
128.4 IPS |
|
|
Style Transfer (SP)
|
100% |
19035
24.5 IPS |
|
|
Style Transfer (HP)
|
100% |
3070
3.95 IPS |
|
|
Style Transfer (Q)
|
98% |
63113
81.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3476
128.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5981
220.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
10234
379.0 IPS |
|
|
Text Classification (SP)
|
71% |
1092
1.58 KIPS |
|
|
Text Classification (HP)
|
71% |
1273
1.84 KIPS |
|
|
Text Classification (Q)
|
92% |
1191
1.60 KIPS |
|
|
Machine Translation (SP)
|
100% |
897
15.4 IPS |
|
|
Machine Translation (HP)
|
96% |
1553
26.8 IPS |
|
|
Machine Translation (Q)
|
100% |
1578
27.2 IPS |
