FPT Elead F22FAH Generic
Geekbench AI Score
2478
Single Precision Score
1106
Half Precision Score
2810
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | rennsport |
| Upload Date | April 18 2025 03:39 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i5-10400 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Generic |
| Motherboard | ASRock H470M-HDV/M.2 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i5-10400 |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 3 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2032
377.8 IPS |
|
|
Image Classification (HP)
|
100% |
413
76.9 IPS |
|
|
Image Classification (Q)
|
96% |
2957
552.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1070
17.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
609
9.86 IPS |
|
|
Image Segmentation (Q)
|
97% |
1459
23.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
3873
4.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
3102
3.62 IPS |
|
|
Pose Estimation (Q)
|
86% |
7484
8.85 IPS |
|
|
Object Detection (SP)
|
100% |
1986
157.5 IPS |
|
|
Object Detection (HP)
|
100% |
509
40.4 IPS |
|
|
Object Detection (Q)
|
58% |
1790
195.6 IPS |
|
|
Face Detection (SP)
|
100% |
2874
34.2 IPS |
|
|
Face Detection (HP)
|
100% |
1077
12.8 IPS |
|
|
Face Detection (Q)
|
96% |
4842
57.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5201
40.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1632
12.6 IPS |
|
|
Depth Estimation (Q)
|
78% |
6473
51.7 IPS |
|
|
Style Transfer (SP)
|
100% |
9696
12.5 IPS |
|
|
Style Transfer (HP)
|
100% |
7620
9.80 IPS |
|
|
Style Transfer (Q)
|
87% |
11152
14.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1871
69.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1516
56.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2242
83.1 IPS |
|
|
Text Classification (SP)
|
100% |
1328
1.77 KIPS |
|
|
Text Classification (HP)
|
100% |
644
860.2 IPS |
|
|
Text Classification (Q)
|
97% |
411
551.0 IPS |
|
|
Machine Translation (SP)
|
100% |
1451
25.0 IPS |
|
|
Machine Translation (HP)
|
100% |
528
9.10 IPS |
|
|
Machine Translation (Q)
|
68% |
1654
32.0 IPS |
