Dell Inc. PowerEdge R610
Geekbench ML Score
49
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux x86 (64-bit)
Result Information
| User | mapmot |
| Upload Date | November 27 2025 12:13 AM |
| Views | 9 |
System Information
| System Information | |
|---|---|
| Operating System | Gentoo Linux |
| Model | Dell Inc. PowerEdge R610 |
| Motherboard | Dell Inc. 0P8FRD |
| CPU Information | |
|---|---|
| Name | Intel Xeon X5675 |
| Topology | 2 Processors, 12 Cores, 24 Threads |
| Identifier | GenuineIntel Family 6 Model 44 Stepping 2 |
| Base Frequency | 3.06 GHz |
| Cluster 1 | 0 Cores |
| L1 Instruction Cache | 32.0 KB x 6 |
| L1 Data Cache | 32.0 KB x 6 |
| L2 Cache | 256 KB x 6 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 78.64 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
31
5.80 IPS |
|
|
Image Classification (F16)
|
100% |
31
5.76 IPS |
|
|
Image Classification (I8)
|
97% |
26
4.84 IPS |
|
|
Image Segmentation (F32)
|
100% |
41
0.68 IPS |
|
|
Image Segmentation (F16)
|
100% |
41
0.68 IPS |
|
|
Image Segmentation (I8)
|
98% |
32
0.54 IPS |
|
|
Pose Estimation (F32)
|
100% |
50
0.06 IPS |
|
|
Pose Estimation (F16)
|
100% |
50
0.06 IPS |
|
|
Pose Estimation (I8)
|
100% |
43
0.05 IPS |
|
|
Object Detection (F32)
|
100% |
32
2.39 IPS |
|
|
Object Detection (F16)
|
100% |
32
2.39 IPS |
|
|
Object Detection (I8)
|
68% |
27
2.03 IPS |
|
|
Face Detection (F32)
|
100% |
101
1.20 IPS |
|
|
Face Detection (F16)
|
100% |
101
1.20 IPS |
|
|
Face Detection (I8)
|
87% |
82
0.97 IPS |
|
|
Depth Estimation (F32)
|
100% |
73
0.57 IPS |
|
|
Depth Estimation (F16)
|
100% |
73
0.57 IPS |
|
|
Depth Estimation (I8)
|
95% |
62
0.48 IPS |
|
|
Style Transfer (F32)
|
100% |
149
0.20 IPS |
|
|
Style Transfer (F16)
|
100% |
149
0.20 IPS |
|
|
Style Transfer (I8)
|
98% |
133
0.17 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
34
1.22 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
34
1.22 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
29
1.03 IPS |
|
|
Text Classification (F32)
|
100% |
35
50.7 IPS |
|
|
Text Classification (F16)
|
100% |
35
50.8 IPS |
|
|
Text Classification (I8)
|
92% |
27
38.3 IPS |
|
|
Machine Translation (F32)
|
100% |
68
1.25 IPS |
|
|
Machine Translation (F16)
|
100% |
69
1.27 IPS |
|
|
Machine Translation (I8)
|
62% |
47
0.86 IPS |
