MacBook Pro (14-inch, Nov 2023)
Geekbench ML Score
11216
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | October 29 2024 07:14 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B83) |
| 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 | 4.05 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% |
6327
1.18 KIPS |
|
|
Image Classification (F16)
|
100% |
6443
1.21 KIPS |
|
|
Image Classification (I8)
|
99% |
6434
1.20 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2984
49.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
2947
49.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
3002
50.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
61468
74.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
64233
77.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
63948
77.4 IPS |
|
|
Object Detection (F32)
|
100% |
4873
363.8 IPS |
|
|
Object Detection (F16)
|
100% |
5050
377.0 IPS |
|
|
Object Detection (I8)
|
97% |
3485
260.2 IPS |
|
|
Face Detection (F32)
|
100% |
20419
242.8 IPS |
|
|
Face Detection (F16)
|
98% |
22792
271.0 IPS |
|
|
Face Detection (I8)
|
97% |
22167
263.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
30527
236.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
32263
250.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
31224
242.1 IPS |
|
|
Style Transfer (F32)
|
100% |
127064
167.1 IPS |
|
|
Style Transfer (F16)
|
100% |
138539
182.2 IPS |
|
|
Style Transfer (I8)
|
100% |
150681
198.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
13975
499.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
13430
479.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
9447
337.4 IPS |
|
|
Text Classification (F32)
|
100% |
2458
3.53 KIPS |
|
|
Text Classification (F16)
|
100% |
4257
6.12 KIPS |
|
|
Text Classification (I8)
|
96% |
4347
6.25 KIPS |
|
|
Machine Translation (F32)
|
100% |
1289
23.7 IPS |
|
|
Machine Translation (F16)
|
100% |
2014
37.1 IPS |
|
|
Machine Translation (I8)
|
99% |
1184
21.8 IPS |
