Dell Inc. Dell Pro Max Tower T2 FCT2250
Geekbench AI Score
45222
Single Precision Score
66152
Half Precision Score
34105
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | November 28 2025 08:45 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA RTX PRO 6000 Blackwell Workstation Edition |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (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% |
15790
2.94 KIPS |
|
|
Image Classification (HP)
|
100% |
20768
3.86 KIPS |
|
|
Image Classification (Q)
|
100% |
13590
2.53 KIPS |
|
|
Image Segmentation (SP)
|
100% |
33924
549.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
40973
664.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
30593
497.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
396772
463.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
980572
1.14 KIPS |
|
|
Pose Estimation (Q)
|
96% |
326128
382.0 IPS |
|
|
Object Detection (SP)
|
100% |
21982
1.74 KIPS |
|
|
Object Detection (HP)
|
100% |
27438
2.18 KIPS |
|
|
Object Detection (Q)
|
84% |
18703
1.51 KIPS |
|
|
Face Detection (SP)
|
100% |
70733
840.5 IPS |
|
|
Face Detection (HP)
|
100% |
87206
1.04 KIPS |
|
|
Face Detection (Q)
|
97% |
59464
709.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
111841
861.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
181069
1.40 KIPS |
|
|
Depth Estimation (Q)
|
77% |
86012
688.9 IPS |
|
|
Style Transfer (SP)
|
100% |
592112
761.2 IPS |
|
|
Style Transfer (HP)
|
100% |
1616850
2.08 KIPS |
|
|
Style Transfer (Q)
|
98% |
527336
680.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
66391
2.45 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
88200
3.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
48817
1.81 KIPS |
|
|
Text Classification (SP)
|
100% |
3808
5.08 KIPS |
|
|
Text Classification (HP)
|
100% |
4832
6.45 KIPS |
|
|
Text Classification (Q)
|
97% |
2195
2.94 KIPS |
|
|
Machine Translation (SP)
|
100% |
6466
111.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6443
111.0 IPS |
|
|
Machine Translation (Q)
|
70% |
2905
54.5 IPS |
