MacBook Air (Late 2020)
Geekbench ML Score
6605
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 23 2024 06:48 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B5024e) |
| 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 | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1150
215.1 IPS |
|
|
Image Classification (F16)
|
100% |
6089
1.14 KIPS |
|
|
Image Classification (I8)
|
99% |
6605
1.24 KIPS |
|
|
Image Segmentation (F32)
|
100% |
800
13.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1085
18.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1095
18.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
15153
18.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
63364
76.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
63070
76.4 IPS |
|
|
Object Detection (F32)
|
100% |
1502
112.1 IPS |
|
|
Object Detection (F16)
|
100% |
4057
302.9 IPS |
|
|
Object Detection (I8)
|
97% |
1676
125.1 IPS |
|
|
Face Detection (F32)
|
100% |
5554
66.0 IPS |
|
|
Face Detection (F16)
|
97% |
12168
144.7 IPS |
|
|
Face Detection (I8)
|
96% |
12078
143.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
10188
79.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
40565
314.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
41422
321.2 IPS |
|
|
Style Transfer (F32)
|
100% |
26480
34.8 IPS |
|
|
Style Transfer (F16)
|
100% |
114656
150.8 IPS |
|
|
Style Transfer (I8)
|
100% |
120173
158.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4894
174.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
23883
853.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
24058
859.2 IPS |
|
|
Text Classification (F32)
|
100% |
2055
2.95 KIPS |
|
|
Text Classification (F16)
|
100% |
3491
5.02 KIPS |
|
|
Text Classification (I8)
|
96% |
3515
5.05 KIPS |
|
|
Machine Translation (F32)
|
100% |
487
8.96 IPS |
|
|
Machine Translation (F16)
|
100% |
1643
30.2 IPS |
|
|
Machine Translation (I8)
|
99% |
503
9.25 IPS |
