MacBook Air (Late 2020)
Geekbench ML Score
6935
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 16 2024 05:16 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | MacBook Air (Late 2020) |
| Model ID | MacBookAir10,1 |
| Motherboard | MacBookAir10,1 |
| CPU Information | |
|---|---|
| Name | Apple M1 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1728
323.3 IPS |
|
|
Image Classification (F16)
|
100% |
6237
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6402
1.20 KIPS |
|
|
Image Segmentation (F32)
|
100% |
834
13.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
3824
63.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
3837
64.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
16176
19.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
62137
75.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
65065
78.8 IPS |
|
|
Object Detection (F32)
|
100% |
1501
112.1 IPS |
|
|
Object Detection (F16)
|
100% |
3847
287.2 IPS |
|
|
Object Detection (I8)
|
97% |
1382
103.1 IPS |
|
|
Face Detection (F32)
|
100% |
6012
71.5 IPS |
|
|
Face Detection (F16)
|
97% |
11654
138.6 IPS |
|
|
Face Detection (I8)
|
96% |
11481
136.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
12062
93.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
39749
308.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
44380
344.2 IPS |
|
|
Style Transfer (F32)
|
100% |
28598
37.6 IPS |
|
|
Style Transfer (F16)
|
100% |
115158
151.5 IPS |
|
|
Style Transfer (I8)
|
100% |
119416
157.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5041
180.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18156
648.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18317
654.2 IPS |
|
|
Text Classification (F32)
|
100% |
1193
1.71 KIPS |
|
|
Text Classification (F16)
|
100% |
2222
3.19 KIPS |
|
|
Text Classification (I8)
|
96% |
2230
3.21 KIPS |
|
|
Machine Translation (F32)
|
100% |
563
10.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1829
33.7 IPS |
|
|
Machine Translation (I8)
|
99% |
563
10.4 IPS |
