MacBook Pro (16-inch, Nov 2023)
Geekbench ML Score
10526
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 05:18 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | MacBook Pro (16-inch, Nov 2023) |
| Model ID | Mac15,9 |
| Motherboard | Mac15,9 |
| CPU Information | |
|---|---|
| Name | Apple M3 Max |
| Topology | 1 Processor, 16 Cores |
| Identifier | Apple M3 Max |
| Base Frequency | 4.05 GHz |
| Cluster 1 | 12 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 | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
7194
1.35 KIPS |
|
|
Image Classification (F16)
|
100% |
7469
1.40 KIPS |
|
|
Image Classification (I8)
|
99% |
7046
1.32 KIPS |
|
|
Image Segmentation (F32)
|
100% |
3109
51.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
3142
52.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
3149
52.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
83827
101.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
87487
105.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
84083
101.8 IPS |
|
|
Object Detection (F32)
|
100% |
4570
341.2 IPS |
|
|
Object Detection (F16)
|
100% |
5343
398.9 IPS |
|
|
Object Detection (I8)
|
97% |
4982
372.0 IPS |
|
|
Face Detection (F32)
|
100% |
23326
277.3 IPS |
|
|
Face Detection (F16)
|
98% |
26568
315.9 IPS |
|
|
Face Detection (I8)
|
97% |
24957
296.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
35490
275.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
37994
294.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
37050
287.3 IPS |
|
|
Style Transfer (F32)
|
100% |
159016
209.2 IPS |
|
|
Style Transfer (F16)
|
100% |
168114
221.1 IPS |
|
|
Style Transfer (I8)
|
100% |
166086
218.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9535
340.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10222
365.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15433
551.2 IPS |
|
|
Text Classification (F32)
|
100% |
1069
1.54 KIPS |
|
|
Text Classification (F16)
|
100% |
800
1.15 KIPS |
|
|
Text Classification (I8)
|
96% |
877
1.26 KIPS |
|
|
Machine Translation (F32)
|
100% |
1136
20.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1146
21.1 IPS |
|
|
Machine Translation (I8)
|
99% |
1059
19.5 IPS |
