Fedora Linux PC System manufacturer System Product Name
Geekbench AI Score
18
Single Precision Score
18
Half Precision Score
14
Quantized Score
Geekbench AI 1.2.0 for Linux x86 (64-bit)
Result Information
| User | MarkTheBench |
| Upload Date | January 12 2025 04:34 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Core i7-870 |
| System Information | |
|---|---|
| Operating System | Fedora Linux 41 (Workstation Edition) |
| Model | System manufacturer System Product Name |
| Motherboard | ASUSTeK Computer INC. P7H57D-V EVO |
| CPU Information | |
|---|---|
| Name | Intel Core i7-870 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 30 Stepping 5 |
| Base Frequency | 2.93 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 11.63 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11
1.95 IPS |
|
|
Image Classification (HP)
|
100% |
10
1.86 IPS |
|
|
Image Classification (Q)
|
97% |
8
1.54 IPS |
|
|
Image Segmentation (SP)
|
100% |
14
0.22 IPS |
|
|
Image Segmentation (HP)
|
100% |
14
0.23 IPS |
|
|
Image Segmentation (Q)
|
98% |
11
0.19 IPS |
|
|
Pose Estimation (SP)
|
100% |
17
0.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
17
0.02 IPS |
|
|
Pose Estimation (Q)
|
96% |
15
0.02 IPS |
|
|
Object Detection (SP)
|
100% |
10
0.81 IPS |
|
|
Object Detection (HP)
|
100% |
10
0.81 IPS |
|
|
Object Detection (Q)
|
87% |
9
0.68 IPS |
|
|
Face Detection (SP)
|
100% |
34
0.40 IPS |
|
|
Face Detection (HP)
|
100% |
34
0.40 IPS |
|
|
Face Detection (Q)
|
97% |
28
0.33 IPS |
|
|
Depth Estimation (SP)
|
100% |
24
0.19 IPS |
|
|
Depth Estimation (HP)
|
99% |
24
0.19 IPS |
|
|
Depth Estimation (Q)
|
64% |
17
0.16 IPS |
|
|
Style Transfer (SP)
|
100% |
51
0.07 IPS |
|
|
Style Transfer (HP)
|
100% |
51
0.07 IPS |
|
|
Style Transfer (Q)
|
98% |
44
0.06 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
11
0.40 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
11
0.40 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
9
0.34 IPS |
|
|
Text Classification (SP)
|
100% |
14
18.4 IPS |
|
|
Text Classification (HP)
|
100% |
14
18.4 IPS |
|
|
Text Classification (Q)
|
91% |
11
14.8 IPS |
|
|
Machine Translation (SP)
|
100% |
26
0.45 IPS |
|
|
Machine Translation (HP)
|
100% |
26
0.45 IPS |
|
|
Machine Translation (Q)
|
58% |
15
0.36 IPS |
