ECS H110H4-CM3
Geekbench ML Score
14
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux x86 (64-bit)
Result Information
| Upload Date | April 30 2024 04:40 AM |
| Views | 40 |
System Information
| System Information | |
|---|---|
| Operating System | Linux Mint 20.3 |
| Model | ECS H110H4-CM3 |
| Motherboard | ECS H110H4-CM3 |
| CPU Information | |
|---|---|
| Name | Intel Core i3-7100 |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 9 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 0 Cores |
| L1 Instruction Cache | 32.0 KB x 2 |
| L1 Data Cache | 32.0 KB x 2 |
| L2 Cache | 256 KB x 2 |
| L3 Cache | 3.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 31.23 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
9
1.70 IPS |
|
|
Image Classification (F16)
|
100% |
9
1.69 IPS |
|
|
Image Classification (I8)
|
97% |
7
1.33 IPS |
|
|
Image Segmentation (F32)
|
100% |
12
0.20 IPS |
|
|
Image Segmentation (F16)
|
100% |
12
0.20 IPS |
|
|
Image Segmentation (I8)
|
98% |
9
0.16 IPS |
|
|
Pose Estimation (F32)
|
100% |
14
0.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
14
0.02 IPS |
|
|
Pose Estimation (I8)
|
100% |
11
0.01 IPS |
|
|
Object Detection (F32)
|
100% |
9
0.70 IPS |
|
|
Object Detection (F16)
|
100% |
9
0.70 IPS |
|
|
Object Detection (I8)
|
68% |
7
0.55 IPS |
|
|
Face Detection (F32)
|
100% |
30
0.36 IPS |
|
|
Face Detection (F16)
|
100% |
30
0.36 IPS |
|
|
Face Detection (I8)
|
87% |
23
0.27 IPS |
|
|
Depth Estimation (F32)
|
100% |
21
0.16 IPS |
|
|
Depth Estimation (F16)
|
100% |
21
0.16 IPS |
|
|
Depth Estimation (I8)
|
95% |
17
0.13 IPS |
|
|
Style Transfer (F32)
|
100% |
44
0.06 IPS |
|
|
Style Transfer (F16)
|
100% |
44
0.06 IPS |
|
|
Style Transfer (I8)
|
98% |
35
0.05 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
10
0.35 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10
0.35 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
8
0.28 IPS |
|
|
Text Classification (F32)
|
100% |
11
16.0 IPS |
|
|
Text Classification (F16)
|
100% |
11
16.1 IPS |
|
|
Text Classification (I8)
|
92% |
9
12.5 IPS |
|
|
Machine Translation (F32)
|
100% |
23
0.43 IPS |
|
|
Machine Translation (F16)
|
100% |
23
0.43 IPS |
|
|
Machine Translation (I8)
|
62% |
17
0.31 IPS |
