Micro-Star International Co., Ltd. Prestige 15 A11SB
Geekbench ML Score
3616
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | Puffin |
| Upload Date | March 03 2024 02:26 AM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Education (64-bit) |
| Model | Micro-Star International Co., Ltd. Prestige 15 A11SB |
| Motherboard | Micro-Star International Co., Ltd. MS-16S6 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-1185G7 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 140 Stepping 1 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 4 |
| L1 Data Cache | 48.0 KB x 4 |
| L2 Cache | 1.25 MB x 4 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce MX450 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1735
324.7 IPS |
|
|
Image Classification (F16)
|
100% |
1725
322.8 IPS |
|
|
Image Classification (I8)
|
100% |
1410
263.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
2342
39.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
2341
39.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1992
33.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
15117
18.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
15465
18.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
13016
15.8 IPS |
|
|
Object Detection (F32)
|
100% |
1696
126.6 IPS |
|
|
Object Detection (F16)
|
100% |
1714
128.0 IPS |
|
|
Object Detection (I8)
|
60% |
1458
108.8 IPS |
|
|
Face Detection (F32)
|
100% |
3290
39.1 IPS |
|
|
Face Detection (F16)
|
100% |
3298
39.2 IPS |
|
|
Face Detection (I8)
|
89% |
2677
31.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
9415
73.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
9431
73.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
7375
57.2 IPS |
|
|
Style Transfer (F32)
|
100% |
36715
48.3 IPS |
|
|
Style Transfer (F16)
|
100% |
36624
48.2 IPS |
|
|
Style Transfer (I8)
|
98% |
28453
37.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6584
235.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6046
215.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3965
141.6 IPS |
|
|
Text Classification (F32)
|
100% |
1064
1.53 KIPS |
|
|
Text Classification (F16)
|
100% |
1102
1.58 KIPS |
|
|
Text Classification (I8)
|
98% |
596
856.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1275
23.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1286
23.7 IPS |
|
|
Machine Translation (I8)
|
70% |
716
13.2 IPS |
