HP 27-a050qd Ubuntu LTS 24.04 HP 27-a050qd
Geekbench AI Score
28
Single Precision Score
28
Half Precision Score
20
Quantized Score
Geekbench AI 1.3.0 for Linux x86 (64-bit)
Result Information
| User | cllee |
| Upload Date | April 04 2025 09:45 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Core i7-6700T |
| System Information | |
|---|---|
| Operating System | Ubuntu 24.04.2 LTS |
| Model | HP 27-a050qd |
| Motherboard | HP 81B7 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-6700T |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 94 Stepping 3 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
16
3.00 IPS |
|
|
Image Classification (HP)
|
100% |
16
3.00 IPS |
|
|
Image Classification (Q)
|
97% |
13
2.36 IPS |
|
|
Image Segmentation (SP)
|
100% |
22
0.35 IPS |
|
|
Image Segmentation (HP)
|
100% |
22
0.35 IPS |
|
|
Image Segmentation (Q)
|
98% |
17
0.28 IPS |
|
|
Pose Estimation (SP)
|
100% |
26
0.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
26
0.03 IPS |
|
|
Pose Estimation (Q)
|
96% |
21
0.02 IPS |
|
|
Object Detection (SP)
|
100% |
16
1.24 IPS |
|
|
Object Detection (HP)
|
100% |
16
1.24 IPS |
|
|
Object Detection (Q)
|
87% |
12
0.98 IPS |
|
|
Face Detection (SP)
|
100% |
53
0.63 IPS |
|
|
Face Detection (HP)
|
100% |
53
0.63 IPS |
|
|
Face Detection (Q)
|
97% |
40
0.48 IPS |
|
|
Depth Estimation (SP)
|
100% |
38
0.29 IPS |
|
|
Depth Estimation (HP)
|
99% |
38
0.29 IPS |
|
|
Depth Estimation (Q)
|
64% |
25
0.23 IPS |
|
|
Style Transfer (SP)
|
100% |
79
0.10 IPS |
|
|
Style Transfer (HP)
|
100% |
79
0.10 IPS |
|
|
Style Transfer (Q)
|
98% |
63
0.08 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
17
0.62 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
17
0.62 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
13
0.49 IPS |
|
|
Text Classification (SP)
|
100% |
21
28.2 IPS |
|
|
Text Classification (HP)
|
100% |
21
28.2 IPS |
|
|
Text Classification (Q)
|
91% |
16
21.4 IPS |
|
|
Machine Translation (SP)
|
100% |
41
0.70 IPS |
|
|
Machine Translation (HP)
|
100% |
41
0.70 IPS |
|
|
Machine Translation (Q)
|
58% |
21
0.51 IPS |
