MacBook Pro (13-inch, 2022)
Geekbench ML Score
9465
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 10 2025 08:44 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.3 (Build 24D5040f) |
| Model | MacBook Pro (13-inch, 2022) |
| Model ID | Mac14,7 |
| Motherboard | Mac14,7 |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M2 |
| Base Frequency | 3.47 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% |
3303
618.1 IPS |
|
|
Image Classification (F16)
|
100% |
9646
1.80 KIPS |
|
|
Image Classification (I8)
|
99% |
10677
2.00 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1392
23.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1869
31.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1900
31.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
23176
28.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
94987
115.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
98218
118.9 IPS |
|
|
Object Detection (F32)
|
100% |
2800
209.1 IPS |
|
|
Object Detection (F16)
|
100% |
5145
384.1 IPS |
|
|
Object Detection (I8)
|
97% |
2698
201.4 IPS |
|
|
Face Detection (F32)
|
100% |
9104
108.2 IPS |
|
|
Face Detection (F16)
|
97% |
20336
241.8 IPS |
|
|
Face Detection (I8)
|
96% |
19970
237.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
16132
125.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
61759
478.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
50632
392.6 IPS |
|
|
Style Transfer (F32)
|
100% |
40795
53.7 IPS |
|
|
Style Transfer (F16)
|
100% |
141482
186.1 IPS |
|
|
Style Transfer (I8)
|
100% |
146436
192.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6895
246.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33854
1.21 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
32769
1.17 KIPS |
|
|
Text Classification (F32)
|
100% |
2060
2.96 KIPS |
|
|
Text Classification (F16)
|
100% |
3346
4.81 KIPS |
|
|
Text Classification (I8)
|
96% |
3316
4.77 KIPS |
|
|
Machine Translation (F32)
|
100% |
588
10.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1350
24.8 IPS |
|
|
Machine Translation (I8)
|
99% |
623
11.5 IPS |
