MacBook Pro (13-inch, 2022)
Geekbench ML Score
9832
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | December 10 2025 07:05 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.2 (Build 25C56) |
| 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% |
3474
650.0 IPS |
|
|
Image Classification (F16)
|
100% |
10250
1.92 KIPS |
|
|
Image Classification (I8)
|
99% |
11513
2.15 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1392
23.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1977
33.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
1468
24.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
22686
27.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
94624
114.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
96199
116.5 IPS |
|
|
Object Detection (F32)
|
100% |
2288
170.8 IPS |
|
|
Object Detection (F16)
|
100% |
4547
339.4 IPS |
|
|
Object Detection (I8)
|
97% |
2854
213.1 IPS |
|
|
Face Detection (F32)
|
100% |
9376
111.5 IPS |
|
|
Face Detection (F16)
|
97% |
20349
241.9 IPS |
|
|
Face Detection (I8)
|
96% |
20217
240.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
16267
126.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
51031
395.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
52421
406.5 IPS |
|
|
Style Transfer (F32)
|
100% |
40809
53.7 IPS |
|
|
Style Transfer (F16)
|
100% |
147811
194.4 IPS |
|
|
Style Transfer (I8)
|
100% |
143565
188.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8200
292.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
35847
1.28 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
36472
1.30 KIPS |
|
|
Text Classification (F32)
|
100% |
2154
3.10 KIPS |
|
|
Text Classification (F16)
|
100% |
3547
5.10 KIPS |
|
|
Text Classification (I8)
|
96% |
3556
5.11 KIPS |
|
|
Machine Translation (F32)
|
100% |
1010
18.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1431
26.3 IPS |
|
|
Machine Translation (I8)
|
99% |
969
17.8 IPS |
