MacBook Pro (13-inch, 2022)
Geekbench ML Score
9571
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | December 09 2024 07:48 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.2 (Build 24C100) |
| 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 | 3.48 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 | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3382
632.8 IPS |
|
|
Image Classification (F16)
|
100% |
9802
1.83 KIPS |
|
|
Image Classification (I8)
|
99% |
11006
2.06 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1373
22.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1992
33.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
2027
33.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
23051
27.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
93406
113.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
97767
118.4 IPS |
|
|
Object Detection (F32)
|
100% |
2873
214.5 IPS |
|
|
Object Detection (F16)
|
100% |
5452
407.1 IPS |
|
|
Object Detection (I8)
|
97% |
1893
141.3 IPS |
|
|
Face Detection (F32)
|
100% |
9013
107.2 IPS |
|
|
Face Detection (F16)
|
97% |
19898
236.6 IPS |
|
|
Face Detection (I8)
|
96% |
19845
236.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
15920
123.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
48836
378.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
46585
361.3 IPS |
|
|
Style Transfer (F32)
|
100% |
41029
54.0 IPS |
|
|
Style Transfer (F16)
|
100% |
146416
192.6 IPS |
|
|
Style Transfer (I8)
|
100% |
148177
194.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8132
290.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
32978
1.18 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34240
1.22 KIPS |
|
|
Text Classification (F32)
|
100% |
2087
3.00 KIPS |
|
|
Text Classification (F16)
|
100% |
3453
4.96 KIPS |
|
|
Text Classification (I8)
|
96% |
3467
4.98 KIPS |
|
|
Machine Translation (F32)
|
100% |
767
14.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1394
25.6 IPS |
|
|
Machine Translation (I8)
|
99% |
756
13.9 IPS |
