QEMU Standard PC (Q35 + ICH9, 2009)
Geekbench AI Score
68
Single Precision Score
68
Half Precision Score
53
Quantized Score
Geekbench AI 1.0.0 for Linux x86 (64-bit)
Result Information
| User | jamiesmithnc |
| Upload Date | August 26 2024 07:26 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Xeon E312xx (Sandy Bridge) |
| System Information | |
|---|---|
| Operating System | Ubuntu 24.04 LTS |
| Model | QEMU Standard PC (Q35 + ICH9, 2009) |
| Motherboard | N/A |
| CPU Information | |
|---|---|
| Name | Intel Xeon E312xx (Sandy Bridge) |
| Topology | 1 Processor, 12 Cores |
| Identifier | GenuineIntel Family 6 Model 42 Stepping 1 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 47.01 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
47
8.65 IPS |
|
|
Image Classification (HP)
|
100% |
43
7.92 IPS |
|
|
Image Classification (Q)
|
97% |
34
6.43 IPS |
|
|
Image Segmentation (SP)
|
100% |
52
0.84 IPS |
|
|
Image Segmentation (HP)
|
100% |
53
0.86 IPS |
|
|
Image Segmentation (Q)
|
98% |
43
0.70 IPS |
|
|
Pose Estimation (SP)
|
100% |
65
0.08 IPS |
|
|
Pose Estimation (HP)
|
100% |
65
0.08 IPS |
|
|
Pose Estimation (Q)
|
96% |
55
0.06 IPS |
|
|
Object Detection (SP)
|
100% |
37
2.93 IPS |
|
|
Object Detection (HP)
|
100% |
37
2.92 IPS |
|
|
Object Detection (Q)
|
88% |
31
2.52 IPS |
|
|
Face Detection (SP)
|
100% |
124
1.47 IPS |
|
|
Face Detection (HP)
|
100% |
124
1.47 IPS |
|
|
Face Detection (Q)
|
97% |
103
1.22 IPS |
|
|
Depth Estimation (SP)
|
100% |
90
0.69 IPS |
|
|
Depth Estimation (HP)
|
100% |
91
0.70 IPS |
|
|
Depth Estimation (Q)
|
75% |
74
0.60 IPS |
|
|
Style Transfer (SP)
|
100% |
196
0.25 IPS |
|
|
Style Transfer (HP)
|
100% |
194
0.25 IPS |
|
|
Style Transfer (Q)
|
98% |
172
0.22 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
43
1.59 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
43
1.58 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
36
1.35 IPS |
|
|
Text Classification (SP)
|
100% |
52
69.3 IPS |
|
|
Text Classification (HP)
|
100% |
52
70.0 IPS |
|
|
Text Classification (Q)
|
91% |
40
53.6 IPS |
|
|
Machine Translation (SP)
|
100% |
80
1.38 IPS |
|
|
Machine Translation (HP)
|
100% |
80
1.37 IPS |
|
|
Machine Translation (Q)
|
58% |
43
1.04 IPS |
