MacBook Pro (14-inch, 2023)
Geekbench ML Score
8608
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 05:34 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.5 (Build 23F79) |
| Model | MacBook Pro (14-inch, 2023) |
| Model ID | Mac14,9 |
| Motherboard | Mac14,9 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.47 GHz |
| Cluster 1 | 6 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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4572
855.5 IPS |
|
|
Image Classification (F16)
|
100% |
6874
1.29 KIPS |
|
|
Image Classification (I8)
|
99% |
8259
1.55 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1956
32.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1866
31.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1846
30.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
34070
41.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
75486
91.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
76792
93.0 IPS |
|
|
Object Detection (F32)
|
100% |
3134
234.0 IPS |
|
|
Object Detection (F16)
|
100% |
3806
284.2 IPS |
|
|
Object Detection (I8)
|
97% |
3100
231.5 IPS |
|
|
Face Detection (F32)
|
100% |
13883
165.1 IPS |
|
|
Face Detection (F16)
|
97% |
11098
132.0 IPS |
|
|
Face Detection (I8)
|
96% |
10976
130.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
21384
165.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
35136
272.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
35376
274.3 IPS |
|
|
Style Transfer (F32)
|
100% |
64874
85.3 IPS |
|
|
Style Transfer (F16)
|
100% |
133718
175.9 IPS |
|
|
Style Transfer (I8)
|
100% |
138029
181.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8816
314.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17915
639.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16500
589.3 IPS |
|
|
Text Classification (F32)
|
100% |
494
710.6 IPS |
|
|
Text Classification (F16)
|
100% |
2457
3.53 KIPS |
|
|
Text Classification (I8)
|
96% |
2707
3.89 KIPS |
|
|
Machine Translation (F32)
|
100% |
936
17.2 IPS |
|
|
Machine Translation (F16)
|
100% |
2426
44.6 IPS |
|
|
Machine Translation (I8)
|
99% |
834
15.4 IPS |
