Dell Inc. Dell Pro Max 14 MC14250
Geekbench AI Score
10619
Single Precision Score
26879
Half Precision Score
33289
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | nithinmohantk |
| Upload Date | February 07 2026 10:49 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) Pro 140T GPU (32GB) (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Dell Inc. Dell Pro Max 14 MC14250 |
| Motherboard | Dell Inc. 0Y5MVY |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 265H |
| Topology | 1 Processor, 16 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
7181
1.34 KIPS |
|
|
Image Classification (HP)
|
100% |
13618
2.53 KIPS |
|
|
Image Classification (Q)
|
100% |
17590
3.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
8966
145.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
23965
388.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
27471
445.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
22871
26.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
107707
125.7 IPS |
|
|
Pose Estimation (Q)
|
97% |
199868
234.0 IPS |
|
|
Object Detection (SP)
|
100% |
7037
558.1 IPS |
|
|
Object Detection (HP)
|
100% |
16163
1.28 KIPS |
|
|
Object Detection (Q)
|
88% |
20961
1.68 KIPS |
|
|
Face Detection (SP)
|
100% |
12960
154.0 IPS |
|
|
Face Detection (HP)
|
100% |
29643
352.2 IPS |
|
|
Face Detection (Q)
|
100% |
41657
495.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
22930
176.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
54953
423.4 IPS |
|
|
Depth Estimation (Q)
|
89% |
72274
561.8 IPS |
|
|
Style Transfer (SP)
|
100% |
49557
63.7 IPS |
|
|
Style Transfer (HP)
|
100% |
191903
246.7 IPS |
|
|
Style Transfer (Q)
|
98% |
319768
412.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
10182
376.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
38123
1.41 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
47653
1.76 KIPS |
|
|
Text Classification (SP)
|
100% |
3240
4.32 KIPS |
|
|
Text Classification (HP)
|
100% |
4921
6.57 KIPS |
|
|
Text Classification (Q)
|
92% |
3177
4.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
3622
62.4 IPS |
|
|
Machine Translation (HP)
|
98% |
5909
102.1 IPS |
|
|
Machine Translation (Q)
|
100% |
5665
97.6 IPS |
