FUJITSU CELSIUS M470-2
Geekbench AI Score
365
Single Precision Score
246
Half Precision Score
546
Quantized Score
Geekbench AI 1.4.0 for Windows x86 (64-bit)
Result Information
| User | Claus7911 |
| Upload Date | November 26 2025 03:22 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Xeon W3565 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | FUJITSU CELSIUS M470-2 |
| Motherboard | FUJITSU D2778-C1 |
| Power Plan | Ausbalanciert |
| CPU Information | |
|---|---|
| Name | Intel Xeon W3565 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 26 Stepping 5 |
| Base Frequency | 3.19 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Type | DDR-2 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
226
42.1 IPS |
|
|
Image Classification (HP)
|
100% |
111
20.6 IPS |
|
|
Image Classification (Q)
|
96% |
414
77.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
210
3.40 IPS |
|
|
Image Segmentation (HP)
|
100% |
157
2.55 IPS |
|
|
Image Segmentation (Q)
|
97% |
459
7.47 IPS |
|
|
Pose Estimation (SP)
|
100% |
439
0.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
418
0.49 IPS |
|
|
Pose Estimation (Q)
|
86% |
769
0.91 IPS |
|
|
Object Detection (SP)
|
100% |
207
16.4 IPS |
|
|
Object Detection (HP)
|
100% |
132
10.5 IPS |
|
|
Object Detection (Q)
|
58% |
298
32.5 IPS |
|
|
Face Detection (SP)
|
100% |
595
7.08 IPS |
|
|
Face Detection (HP)
|
100% |
309
3.67 IPS |
|
|
Face Detection (Q)
|
96% |
868
10.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
576
4.44 IPS |
|
|
Depth Estimation (HP)
|
99% |
349
2.69 IPS |
|
|
Depth Estimation (Q)
|
78% |
872
6.94 IPS |
|
|
Style Transfer (SP)
|
100% |
1114
1.43 IPS |
|
|
Style Transfer (HP)
|
100% |
1152
1.48 IPS |
|
|
Style Transfer (Q)
|
87% |
1606
2.09 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
247
9.10 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
232
8.57 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
441
16.3 IPS |
|
|
Text Classification (SP)
|
100% |
291
388.4 IPS |
|
|
Text Classification (HP)
|
100% |
158
211.5 IPS |
|
|
Text Classification (Q)
|
97% |
191
255.3 IPS |
|
|
Machine Translation (SP)
|
100% |
357
6.15 IPS |
|
|
Machine Translation (HP)
|
100% |
188
3.23 IPS |
|
|
Machine Translation (Q)
|
68% |
532
10.3 IPS |
