Timi TM1604
Geekbench ML Score
312
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| User | grinceur |
| Upload Date | August 17 2024 12:22 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Arch Linux |
| Model | Timi TM1604 |
| Motherboard | Timi TM1604 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-7200U |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 142 Stepping 9 |
| Base Frequency | 3.10 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 | 7.67 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
203
38.0 IPS |
|
|
Image Classification (F16)
|
100% |
202
37.8 IPS |
|
|
Image Classification (I8)
|
99% |
161
30.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
268
4.47 IPS |
|
|
Image Segmentation (F16)
|
100% |
279
4.66 IPS |
|
|
Image Segmentation (I8)
|
98% |
193
3.22 IPS |
|
|
Pose Estimation (F32)
|
100% |
348
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
315
0.38 IPS |
|
|
Pose Estimation (I8)
|
100% |
371
0.45 IPS |
|
|
Object Detection (F32)
|
100% |
233
17.4 IPS |
|
|
Object Detection (F16)
|
100% |
211
15.8 IPS |
|
|
Object Detection (I8)
|
65% |
192
14.3 IPS |
|
|
Face Detection (F32)
|
100% |
396
4.71 IPS |
|
|
Face Detection (F16)
|
100% |
428
5.09 IPS |
|
|
Face Detection (I8)
|
87% |
379
4.50 IPS |
|
|
Depth Estimation (F32)
|
100% |
417
3.23 IPS |
|
|
Depth Estimation (F16)
|
100% |
408
3.17 IPS |
|
|
Depth Estimation (I8)
|
95% |
406
3.15 IPS |
|
|
Style Transfer (F32)
|
100% |
578
0.76 IPS |
|
|
Style Transfer (F16)
|
100% |
583
0.77 IPS |
|
|
Style Transfer (I8)
|
98% |
801
1.05 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
220
7.84 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
242
8.63 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
270
9.63 IPS |
|
|
Text Classification (F32)
|
100% |
351
504.7 IPS |
|
|
Text Classification (F16)
|
100% |
434
623.7 IPS |
|
|
Text Classification (I8)
|
92% |
124
178.8 IPS |
|
|
Machine Translation (F32)
|
100% |
475
8.75 IPS |
|
|
Machine Translation (F16)
|
100% |
507
9.33 IPS |
|
|
Machine Translation (I8)
|
62% |
247
4.55 IPS |
