Dell Pro Max Tower T2 FCT2250 OpenVINO iGPU Dell Inc. Dell Pro Max Tower T2 FCT2250
Geekbench AI Score
5404
Single Precision Score
8459
Half Precision Score
12754
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | jrybolt |
| Upload Date | June 17 2025 08:22 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Dell Inc. Dell Pro Max Tower T2 FCT2250 |
| Motherboard | Dell Inc. 0D8XDK |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 265K |
| Topology | 1 Processor, 20 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3727
693.1 IPS |
|
|
Image Classification (HP)
|
100% |
5544
1.03 KIPS |
|
|
Image Classification (Q)
|
100% |
7342
1.37 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3780
61.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
8524
138.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
11897
192.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
11545
13.5 IPS |
|
|
Pose Estimation (HP)
|
99% |
10753
12.6 IPS |
|
|
Pose Estimation (Q)
|
97% |
34930
40.9 IPS |
|
|
Object Detection (SP)
|
100% |
3453
273.9 IPS |
|
|
Object Detection (HP)
|
100% |
5336
423.3 IPS |
|
|
Object Detection (Q)
|
88% |
8775
703.2 IPS |
|
|
Face Detection (SP)
|
100% |
7339
87.2 IPS |
|
|
Face Detection (HP)
|
100% |
14276
169.6 IPS |
|
|
Face Detection (Q)
|
100% |
22402
266.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
11975
92.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
20934
161.8 IPS |
|
|
Depth Estimation (Q)
|
89% |
23957
186.2 IPS |
|
|
Style Transfer (SP)
|
100% |
28450
36.6 IPS |
|
|
Style Transfer (HP)
|
100% |
38006
48.9 IPS |
|
|
Style Transfer (Q)
|
98% |
80006
103.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5016
185.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8958
330.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
14032
519.7 IPS |
|
|
Text Classification (SP)
|
71% |
1463
2.12 KIPS |
|
|
Text Classification (HP)
|
71% |
2316
3.35 KIPS |
|
|
Text Classification (Q)
|
92% |
2413
3.24 KIPS |
|
|
Machine Translation (SP)
|
100% |
2062
35.5 IPS |
|
|
Machine Translation (HP)
|
96% |
2936
50.8 IPS |
|
|
Machine Translation (Q)
|
100% |
2927
50.4 IPS |
