MacBook Pro (14-inch, Nov 2023)
Geekbench ML Score
9406
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | March 28 2024 04:33 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4.1 (Build 23E224) |
| Model | MacBook Pro (14-inch, Nov 2023) |
| Model ID | Mac15,10 |
| Motherboard | Mac15,10 |
| CPU Information | |
|---|---|
| Name | Apple M3 Max |
| Topology | 1 Processor, 14 Cores |
| Identifier | Apple M3 Max |
| Base Frequency | 3.94 GHz |
| Cluster 1 | 10 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 | 36.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6670
1.25 KIPS |
|
|
Image Classification (F16)
|
100% |
6972
1.30 KIPS |
|
|
Image Classification (I8)
|
99% |
6193
1.16 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2646
44.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
2755
46.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
2758
46.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
63201
76.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
66454
80.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
64202
77.7 IPS |
|
|
Object Detection (F32)
|
100% |
4773
356.3 IPS |
|
|
Object Detection (F16)
|
100% |
5041
376.4 IPS |
|
|
Object Detection (I8)
|
97% |
4671
348.7 IPS |
|
|
Face Detection (F32)
|
100% |
21760
258.7 IPS |
|
|
Face Detection (F16)
|
98% |
24459
290.8 IPS |
|
|
Face Detection (I8)
|
97% |
21380
254.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
32411
251.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
32880
255.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
31339
243.0 IPS |
|
|
Style Transfer (F32)
|
100% |
134401
176.8 IPS |
|
|
Style Transfer (F16)
|
100% |
146957
193.3 IPS |
|
|
Style Transfer (I8)
|
100% |
135598
178.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
13754
491.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10367
370.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
10765
384.4 IPS |
|
|
Text Classification (F32)
|
100% |
684
983.1 IPS |
|
|
Text Classification (F16)
|
100% |
915
1.31 KIPS |
|
|
Text Classification (I8)
|
96% |
642
922.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1098
20.2 IPS |
|
|
Machine Translation (F16)
|
99% |
1161
21.4 IPS |
|
|
Machine Translation (I8)
|
99% |
1136
20.9 IPS |
