MacBook Pro (13-inch, 2022)
Geekbench ML Score
10284
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | March 01 2026 08:31 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.4 (Build 25E5218f) |
| 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 | 3.08 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% |
3388
634.0 IPS |
|
|
Image Classification (F16)
|
100% |
9605
1.80 KIPS |
|
|
Image Classification (I8)
|
99% |
11509
2.15 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1418
23.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1592
26.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1683
28.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
23151
28.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
86515
104.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
88075
106.7 IPS |
|
|
Object Detection (F32)
|
100% |
2774
207.1 IPS |
|
|
Object Detection (F16)
|
100% |
5685
424.4 IPS |
|
|
Object Detection (I8)
|
97% |
2870
214.3 IPS |
|
|
Face Detection (F32)
|
100% |
9480
112.7 IPS |
|
|
Face Detection (F16)
|
98% |
18134
215.6 IPS |
|
|
Face Detection (I8)
|
97% |
19998
237.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
16528
128.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
47458
368.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
52939
410.5 IPS |
|
|
Style Transfer (F32)
|
100% |
40381
53.1 IPS |
|
|
Style Transfer (F16)
|
100% |
137640
181.1 IPS |
|
|
Style Transfer (I8)
|
100% |
152099
200.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6853
244.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
34079
1.22 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34656
1.24 KIPS |
|
|
Text Classification (F32)
|
100% |
3650
5.25 KIPS |
|
|
Text Classification (F16)
|
100% |
5611
8.06 KIPS |
|
|
Text Classification (I8)
|
96% |
5597
8.04 KIPS |
|
|
Machine Translation (F32)
|
100% |
1158
21.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1404
25.8 IPS |
|
|
Machine Translation (I8)
|
99% |
1123
20.7 IPS |
