MacBook Pro (14-inch, Nov 2023)
Geekbench ML Score
7943
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | May 09 2024 05:45 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4.1 (Build 23E224) |
| Model | MacBook Pro (14-inch, Nov 2023) |
| Model ID | Mac15,3 |
| Motherboard | Mac15,3 |
| CPU Information | |
|---|---|
| Name | Apple M3 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M3 |
| Base Frequency | 4.05 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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4135
773.8 IPS |
|
|
Image Classification (F16)
|
100% |
7418
1.39 KIPS |
|
|
Image Classification (I8)
|
99% |
7758
1.45 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1686
28.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
2150
35.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
2054
34.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
23664
28.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
96343
116.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
97524
118.1 IPS |
|
|
Object Detection (F32)
|
100% |
2446
182.6 IPS |
|
|
Object Detection (F16)
|
100% |
5215
389.4 IPS |
|
|
Object Detection (I8)
|
97% |
2840
212.0 IPS |
|
|
Face Detection (F32)
|
100% |
10348
123.0 IPS |
|
|
Face Detection (F16)
|
97% |
12841
152.7 IPS |
|
|
Face Detection (I8)
|
96% |
12797
152.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
15882
123.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
42493
329.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
49241
381.9 IPS |
|
|
Style Transfer (F32)
|
100% |
48868
64.3 IPS |
|
|
Style Transfer (F16)
|
100% |
150102
197.4 IPS |
|
|
Style Transfer (I8)
|
100% |
148685
195.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6997
249.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
20206
721.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18294
653.3 IPS |
|
|
Text Classification (F32)
|
100% |
522
750.7 IPS |
|
|
Text Classification (F16)
|
100% |
680
977.9 IPS |
|
|
Text Classification (I8)
|
96% |
681
978.5 IPS |
|
|
Machine Translation (F32)
|
100% |
802
14.8 IPS |
|
|
Machine Translation (F16)
|
100% |
3155
58.1 IPS |
|
|
Machine Translation (I8)
|
99% |
718
13.2 IPS |
