FUJITSU FUTRO S940
Geekbench AI Score
13
Single Precision Score
13
Half Precision Score
10
Quantized Score
Geekbench AI 1.5.0 for Linux x86 (64-bit)
Result Information
| User | janushk |
| Upload Date | December 02 2025 01:50 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Pentium Silver J5005 |
| System Information | |
|---|---|
| Operating System | Fedora Linux 42 (Server Edition) |
| Model | FUJITSU FUTRO S940 |
| Motherboard | FUJITSU D3543-A1 |
| CPU Information | |
|---|---|
| Name | Intel Pentium Silver J5005 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 122 Stepping 1 |
| Base Frequency | 2.80 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.38 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
8
1.48 IPS |
|
|
Image Classification (HP)
|
100% |
8
1.46 IPS |
|
|
Image Classification (Q)
|
97% |
6
1.20 IPS |
|
|
Image Segmentation (SP)
|
100% |
11
0.17 IPS |
|
|
Image Segmentation (HP)
|
100% |
11
0.17 IPS |
|
|
Image Segmentation (Q)
|
98% |
9
0.14 IPS |
|
|
Pose Estimation (SP)
|
100% |
12
0.01 IPS |
|
|
Pose Estimation (HP)
|
100% |
12
0.01 IPS |
|
|
Pose Estimation (Q)
|
96% |
10
0.01 IPS |
|
|
Object Detection (SP)
|
100% |
8
0.60 IPS |
|
|
Object Detection (HP)
|
100% |
8
0.60 IPS |
|
|
Object Detection (Q)
|
87% |
6
0.50 IPS |
|
|
Face Detection (SP)
|
100% |
25
0.30 IPS |
|
|
Face Detection (HP)
|
100% |
25
0.30 IPS |
|
|
Face Detection (Q)
|
97% |
20
0.24 IPS |
|
|
Depth Estimation (SP)
|
100% |
18
0.14 IPS |
|
|
Depth Estimation (HP)
|
99% |
18
0.14 IPS |
|
|
Depth Estimation (Q)
|
64% |
13
0.12 IPS |
|
|
Style Transfer (SP)
|
100% |
38
0.05 IPS |
|
|
Style Transfer (HP)
|
100% |
38
0.05 IPS |
|
|
Style Transfer (Q)
|
98% |
32
0.04 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
8
0.30 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8
0.30 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
7
0.25 IPS |
|
|
Text Classification (SP)
|
100% |
11
14.1 IPS |
|
|
Text Classification (HP)
|
100% |
11
14.1 IPS |
|
|
Text Classification (Q)
|
91% |
8
10.9 IPS |
|
|
Machine Translation (SP)
|
100% |
20
0.34 IPS |
|
|
Machine Translation (HP)
|
100% |
20
0.34 IPS |
|
|
Machine Translation (Q)
|
58% |
11
0.26 IPS |
