FUJITSU FUTRO S940
Geekbench AI Score
195
Single Precision Score
196
Half Precision Score
669
Quantized Score
Geekbench AI 1.5.0 for Linux x86 (64-bit)
Result Information
| User | janushk |
| Upload Date | December 03 2025 12:51 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Pentium(R) Silver J5005 CPU @ 1.50GHz |
| 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% |
203
37.7 IPS |
|
|
Image Classification (HP)
|
100% |
204
37.9 IPS |
|
|
Image Classification (Q)
|
100% |
448
83.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
254
4.12 IPS |
|
|
Image Segmentation (HP)
|
100% |
255
4.13 IPS |
|
|
Image Segmentation (Q)
|
99% |
526
8.55 IPS |
|
|
Pose Estimation (SP)
|
100% |
357
0.42 IPS |
|
|
Pose Estimation (HP)
|
100% |
359
0.42 IPS |
|
|
Pose Estimation (Q)
|
94% |
886
1.04 IPS |
|
|
Object Detection (SP)
|
100% |
198
15.7 IPS |
|
|
Object Detection (HP)
|
100% |
198
15.7 IPS |
|
|
Object Detection (Q)
|
87% |
449
36.0 IPS |
|
|
Face Detection (SP)
|
100% |
635
7.54 IPS |
|
|
Face Detection (HP)
|
100% |
638
7.58 IPS |
|
|
Face Detection (Q)
|
97% |
1278
15.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
529
4.07 IPS |
|
|
Depth Estimation (HP)
|
99% |
526
4.06 IPS |
|
|
Depth Estimation (Q)
|
81% |
1147
9.06 IPS |
|
|
Style Transfer (SP)
|
100% |
5
0.01 IPS |
|
|
Style Transfer (HP)
|
100% |
5
0.01 IPS |
|
|
Style Transfer (Q)
|
98% |
2874
3.71 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
237
8.74 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
241
8.89 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
589
21.8 IPS |
|
|
Text Classification (SP)
|
100% |
209
279.3 IPS |
|
|
Text Classification (HP)
|
100% |
211
281.5 IPS |
|
|
Text Classification (Q)
|
91% |
286
384.9 IPS |
|
|
Machine Translation (SP)
|
100% |
272
4.68 IPS |
|
|
Machine Translation (HP)
|
100% |
275
4.73 IPS |
|
|
Machine Translation (Q)
|
100% |
272
4.68 IPS |
