MONSTER TULPAR T7 V26.2
Geekbench AI Score
16163
Single Precision Score
30383
Half Precision Score
12833
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | September 03 2025 10:18 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5060 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | MONSTER TULPAR T7 V26.2 |
| Motherboard | MONSTER TULPAR T7 V26.2 |
| Power Plan | Dengeli |
| CPU Information | |
|---|---|
| Name | Intel Core i7-13620H |
| Topology | 1 Processor, 10 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6112
1.14 KIPS |
|
|
Image Classification (HP)
|
100% |
12483
2.32 KIPS |
|
|
Image Classification (Q)
|
99% |
5759
1.07 KIPS |
|
|
Image Segmentation (SP)
|
100% |
10740
174.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
16419
266.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
10409
169.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
76757
89.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
248348
289.8 IPS |
|
|
Pose Estimation (Q)
|
96% |
68854
80.7 IPS |
|
|
Object Detection (SP)
|
100% |
8329
660.7 IPS |
|
|
Object Detection (HP)
|
100% |
15842
1.26 KIPS |
|
|
Object Detection (Q)
|
87% |
7671
615.6 IPS |
|
|
Face Detection (SP)
|
100% |
21382
254.1 IPS |
|
|
Face Detection (HP)
|
100% |
33821
401.9 IPS |
|
|
Face Detection (Q)
|
97% |
19169
228.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
39730
306.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
90427
696.7 IPS |
|
|
Depth Estimation (Q)
|
77% |
33944
271.4 IPS |
|
|
Style Transfer (SP)
|
100% |
126443
162.5 IPS |
|
|
Style Transfer (HP)
|
100% |
404179
519.6 IPS |
|
|
Style Transfer (Q)
|
98% |
109168
140.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
22062
814.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
40876
1.51 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
17740
656.9 IPS |
|
|
Text Classification (SP)
|
100% |
3212
4.29 KIPS |
|
|
Text Classification (HP)
|
100% |
3939
5.26 KIPS |
|
|
Text Classification (Q)
|
97% |
1934
2.59 KIPS |
|
|
Machine Translation (SP)
|
100% |
3811
65.7 IPS |
|
|
Machine Translation (HP)
|
100% |
4178
72.0 IPS |
|
|
Machine Translation (Q)
|
70% |
1570
29.5 IPS |
