Dell Pro Max Tower T2 FCT2250 ONYX CPU Dell Inc. Dell Pro Max Tower T2 FCT2250
Geekbench AI Score
6858
Single Precision Score
2322
Half Precision Score
10045
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | jrybolt |
| Upload Date | June 17 2025 08:12 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 7 265K |
| 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% |
5216
970.0 IPS |
|
|
Image Classification (HP)
|
100% |
775
144.1 IPS |
|
|
Image Classification (Q)
|
99% |
9406
1.75 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2858
46.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1499
24.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
5663
92.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
14060
16.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
8128
9.48 IPS |
|
|
Pose Estimation (Q)
|
94% |
44661
52.4 IPS |
|
|
Object Detection (SP)
|
100% |
4773
378.6 IPS |
|
|
Object Detection (HP)
|
100% |
876
69.5 IPS |
|
|
Object Detection (Q)
|
86% |
11188
899.2 IPS |
|
|
Face Detection (SP)
|
100% |
12879
153.0 IPS |
|
|
Face Detection (HP)
|
100% |
2043
24.3 IPS |
|
|
Face Detection (Q)
|
97% |
13353
159.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
15834
122.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3380
26.0 IPS |
|
|
Depth Estimation (Q)
|
78% |
21682
173.0 IPS |
|
|
Style Transfer (SP)
|
100% |
31918
41.0 IPS |
|
|
Style Transfer (HP)
|
100% |
20346
26.2 IPS |
|
|
Style Transfer (Q)
|
98% |
22807
29.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5301
195.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3581
132.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6876
254.6 IPS |
|
|
Text Classification (SP)
|
100% |
2061
2.75 KIPS |
|
|
Text Classification (HP)
|
100% |
922
1.23 KIPS |
|
|
Text Classification (Q)
|
97% |
1767
2.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
3237
55.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1191
20.5 IPS |
|
|
Machine Translation (Q)
|
65% |
4900
98.5 IPS |
