Dell Inc. Dell Pro Max Tower T2 FCT2250
Geekbench AI Score
45629
Single Precision Score
66514
Half Precision Score
34484
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | December 04 2025 09:48 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA RTX PRO 6000 Blackwell Workstation Edition |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Enterprise (64-bit) |
| Model | Dell Inc. Dell Pro Max Tower T2 FCT2250 |
| Motherboard | Dell Inc. 02RY37 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 285K |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 128.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
16319
3.03 KIPS |
|
|
Image Classification (HP)
|
100% |
20587
3.83 KIPS |
|
|
Image Classification (Q)
|
100% |
13931
2.59 KIPS |
|
|
Image Segmentation (SP)
|
100% |
33936
550.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
40567
657.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
30463
495.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
386728
451.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
967761
1.13 KIPS |
|
|
Pose Estimation (Q)
|
96% |
312469
366.0 IPS |
|
|
Object Detection (SP)
|
100% |
22026
1.75 KIPS |
|
|
Object Detection (HP)
|
100% |
27499
2.18 KIPS |
|
|
Object Detection (Q)
|
84% |
18497
1.49 KIPS |
|
|
Face Detection (SP)
|
100% |
71736
852.4 IPS |
|
|
Face Detection (HP)
|
100% |
89176
1.06 KIPS |
|
|
Face Detection (Q)
|
97% |
59666
711.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
117553
905.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
189804
1.46 KIPS |
|
|
Depth Estimation (Q)
|
77% |
89619
717.8 IPS |
|
|
Style Transfer (SP)
|
100% |
615689
791.5 IPS |
|
|
Style Transfer (HP)
|
100% |
1619981
2.08 KIPS |
|
|
Style Transfer (Q)
|
98% |
539700
695.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
65946
2.44 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
88332
3.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
48903
1.81 KIPS |
|
|
Text Classification (SP)
|
100% |
3690
4.93 KIPS |
|
|
Text Classification (HP)
|
100% |
4745
6.33 KIPS |
|
|
Text Classification (Q)
|
97% |
2256
3.02 KIPS |
|
|
Machine Translation (SP)
|
100% |
6564
113.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6636
114.3 IPS |
|
|
Machine Translation (Q)
|
70% |
3045
57.1 IPS |
