MacBook Air (15-inch, 2023)
Geekbench ML Score
7096
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 17 2024 06:26 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | MacBook Air (15-inch, 2023) |
| Model ID | Mac14,15 |
| Motherboard | Mac14,15 |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M2 |
| Base Frequency | 3.48 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% |
3459
647.3 IPS |
|
|
Image Classification (F16)
|
100% |
6641
1.24 KIPS |
|
|
Image Classification (I8)
|
99% |
6851
1.28 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1370
22.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1570
26.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1555
26.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
23490
28.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
80765
97.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
85543
103.6 IPS |
|
|
Object Detection (F32)
|
100% |
2883
215.2 IPS |
|
|
Object Detection (F16)
|
100% |
3916
292.4 IPS |
|
|
Object Detection (I8)
|
97% |
2652
198.0 IPS |
|
|
Face Detection (F32)
|
100% |
9260
110.1 IPS |
|
|
Face Detection (F16)
|
97% |
10033
119.3 IPS |
|
|
Face Detection (I8)
|
96% |
10828
128.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
16341
126.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
35469
275.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
37530
291.0 IPS |
|
|
Style Transfer (F32)
|
100% |
40933
53.8 IPS |
|
|
Style Transfer (F16)
|
100% |
130320
171.4 IPS |
|
|
Style Transfer (I8)
|
100% |
132452
174.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7020
250.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17345
619.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18272
652.6 IPS |
|
|
Text Classification (F32)
|
100% |
1000
1.44 KIPS |
|
|
Text Classification (F16)
|
100% |
710
1.02 KIPS |
|
|
Text Classification (I8)
|
96% |
710
1.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
662
12.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1854
34.1 IPS |
|
|
Machine Translation (I8)
|
99% |
625
11.5 IPS |
