Microsoft Corporation Surface Go 3
Geekbench ML Score
713
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | Puffin |
| Upload Date | March 03 2024 01:55 AM |
| Views | 15 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Microsoft Corporation Surface Go 3 |
| Motherboard | Microsoft Corporation Surface Go 3 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Pentium(R) CPU GOLD 6500Y @ 1.10GHz |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 142 Stepping 9 |
| Base Frequency | 1.61 GHz |
| Cluster 1 | 2 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 | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
367
68.7 IPS |
|
|
Image Classification (F16)
|
100% |
356
66.7 IPS |
|
|
Image Classification (I8)
|
97% |
454
84.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
264
4.41 IPS |
|
|
Image Segmentation (F16)
|
100% |
335
5.59 IPS |
|
|
Image Segmentation (I8)
|
97% |
406
6.78 IPS |
|
|
Pose Estimation (F32)
|
100% |
696
0.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
834
1.01 IPS |
|
|
Pose Estimation (I8)
|
100% |
1287
1.56 IPS |
|
|
Object Detection (F32)
|
100% |
384
28.7 IPS |
|
|
Object Detection (F16)
|
100% |
419
31.2 IPS |
|
|
Object Detection (I8)
|
60% |
468
35.0 IPS |
|
|
Face Detection (F32)
|
100% |
866
10.3 IPS |
|
|
Face Detection (F16)
|
100% |
895
10.6 IPS |
|
|
Face Detection (I8)
|
87% |
1118
13.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1232
9.56 IPS |
|
|
Depth Estimation (F16)
|
100% |
1296
10.0 IPS |
|
|
Depth Estimation (I8)
|
74% |
1919
14.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2523
3.32 IPS |
|
|
Style Transfer (F16)
|
100% |
2536
3.34 IPS |
|
|
Style Transfer (I8)
|
85% |
3565
4.69 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
621
22.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
618
22.1 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
871
31.1 IPS |
|
|
Text Classification (F32)
|
100% |
462
663.5 IPS |
|
|
Text Classification (F16)
|
100% |
440
632.6 IPS |
|
|
Text Classification (I8)
|
94% |
208
299.1 IPS |
|
|
Machine Translation (F32)
|
100% |
748
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
720
13.2 IPS |
|
|
Machine Translation (I8)
|
67% |
715
13.2 IPS |
