Dell Pro Max Tower T2 FCT2250 OpenVINO NPU Dell Inc. Dell Pro Max Tower T2 FCT2250
Geekbench AI Score
7014
Single Precision Score
9773
Half Precision Score
14979
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | jrybolt |
| Upload Date | June 17 2025 08:24 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| 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% |
4374
813.5 IPS |
|
|
Image Classification (HP)
|
100% |
7068
1.31 KIPS |
|
|
Image Classification (Q)
|
100% |
9558
1.78 KIPS |
|
|
Image Segmentation (SP)
|
100% |
5594
90.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2898
47.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
3916
63.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8278
9.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
33863
39.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
74724
87.5 IPS |
|
|
Object Detection (SP)
|
100% |
4058
321.9 IPS |
|
|
Object Detection (HP)
|
100% |
6087
482.8 IPS |
|
|
Object Detection (Q)
|
87% |
9984
801.3 IPS |
|
|
Face Detection (SP)
|
100% |
11323
134.5 IPS |
|
|
Face Detection (HP)
|
100% |
16114
191.5 IPS |
|
|
Face Detection (Q)
|
100% |
28320
336.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
10478
80.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
18172
140.0 IPS |
|
|
Depth Estimation (Q)
|
88% |
33716
262.3 IPS |
|
|
Style Transfer (SP)
|
100% |
25145
32.3 IPS |
|
|
Style Transfer (HP)
|
100% |
51114
65.7 IPS |
|
|
Style Transfer (Q)
|
98% |
94338
121.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5147
190.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
14192
524.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
25666
950.5 IPS |
|
|
Text Classification (SP)
|
100% |
4134
5.52 KIPS |
|
|
Text Classification (HP)
|
100% |
2046
2.73 KIPS |
|
|
Text Classification (Q)
|
92% |
2015
2.71 KIPS |
|
|
Machine Translation (SP)
|
100% |
5527
95.2 IPS |
|
|
Machine Translation (HP)
|
100% |
4336
74.7 IPS |
|
|
Machine Translation (Q)
|
100% |
4373
75.3 IPS |
