Supermicro X9SCL/X9SCM
Geekbench AI Score
28
Single Precision Score
28
Half Precision Score
20
Quantized Score
Geekbench AI 1.3.0 for Linux x86 (64-bit)
Result Information
| User | Alex647 |
| Upload Date | April 25 2025 10:36 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Xeon E3-1270 V2 |
| System Information | |
|---|---|
| Operating System | Debian GNU/Linux 12 (bookworm) |
| Model | Supermicro X9SCL/X9SCM |
| Motherboard | Supermicro X9SCL/X9SCM |
| CPU Information | |
|---|---|
| Name | Intel Xeon E3-1270 V2 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 58 Stepping 9 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 3.79 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
16
3.00 IPS |
|
|
Image Classification (HP)
|
100% |
16
3.00 IPS |
|
|
Image Classification (Q)
|
97% |
12
2.32 IPS |
|
|
Image Segmentation (SP)
|
100% |
22
0.35 IPS |
|
|
Image Segmentation (HP)
|
100% |
22
0.35 IPS |
|
|
Image Segmentation (Q)
|
98% |
17
0.27 IPS |
|
|
Pose Estimation (SP)
|
100% |
26
0.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
26
0.03 IPS |
|
|
Pose Estimation (Q)
|
96% |
20
0.02 IPS |
|
|
Object Detection (SP)
|
100% |
16
1.24 IPS |
|
|
Object Detection (HP)
|
100% |
16
1.24 IPS |
|
|
Object Detection (Q)
|
87% |
12
0.96 IPS |
|
|
Face Detection (SP)
|
100% |
52
0.62 IPS |
|
|
Face Detection (HP)
|
100% |
52
0.62 IPS |
|
|
Face Detection (Q)
|
97% |
39
0.47 IPS |
|
|
Depth Estimation (SP)
|
100% |
38
0.29 IPS |
|
|
Depth Estimation (HP)
|
99% |
38
0.29 IPS |
|
|
Depth Estimation (Q)
|
64% |
24
0.22 IPS |
|
|
Style Transfer (SP)
|
100% |
79
0.10 IPS |
|
|
Style Transfer (HP)
|
100% |
79
0.10 IPS |
|
|
Style Transfer (Q)
|
98% |
62
0.08 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
17
0.62 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
17
0.62 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
13
0.48 IPS |
|
|
Text Classification (SP)
|
100% |
21
28.2 IPS |
|
|
Text Classification (HP)
|
100% |
21
28.2 IPS |
|
|
Text Classification (Q)
|
91% |
15
20.8 IPS |
|
|
Machine Translation (SP)
|
100% |
41
0.70 IPS |
|
|
Machine Translation (HP)
|
100% |
41
0.70 IPS |
|
|
Machine Translation (Q)
|
58% |
21
0.50 IPS |
