MacBook Pro (13-inch, 2022)
Geekbench ML Score
9437
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 04 2025 06:56 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 26.0 (Build 25A5316i) |
| 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% |
3440
643.6 IPS |
|
|
Image Classification (F16)
|
100% |
10315
1.93 KIPS |
|
|
Image Classification (I8)
|
99% |
9168
1.72 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1138
19.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1636
27.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1658
27.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
22869
27.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
89119
107.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
85609
103.7 IPS |
|
|
Object Detection (F32)
|
100% |
1958
146.2 IPS |
|
|
Object Detection (F16)
|
100% |
5577
416.4 IPS |
|
|
Object Detection (I8)
|
97% |
2664
198.9 IPS |
|
|
Face Detection (F32)
|
100% |
9045
107.5 IPS |
|
|
Face Detection (F16)
|
97% |
17040
202.6 IPS |
|
|
Face Detection (I8)
|
96% |
17354
206.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
15963
123.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
60394
468.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
63819
494.9 IPS |
|
|
Style Transfer (F32)
|
100% |
40473
53.2 IPS |
|
|
Style Transfer (F16)
|
100% |
148304
195.1 IPS |
|
|
Style Transfer (I8)
|
100% |
133391
175.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8341
297.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33386
1.19 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
33580
1.20 KIPS |
|
|
Text Classification (F32)
|
100% |
2115
3.04 KIPS |
|
|
Text Classification (F16)
|
100% |
3448
4.96 KIPS |
|
|
Text Classification (I8)
|
96% |
3467
4.98 KIPS |
|
|
Machine Translation (F32)
|
100% |
922
17.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1327
24.4 IPS |
|
|
Machine Translation (I8)
|
99% |
906
16.7 IPS |
