MacBook Pro (16-inch, 2023)
Geekbench AI Score
4169
Single Precision Score
6767
Half Precision Score
5367
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| Upload Date | September 18 2024 01:27 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.0 (Build 24A335) |
| Model | MacBook Pro (16-inch, 2023) |
| Model ID | Mac14,6 |
| Motherboard | Mac14,6 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.67 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1389
258.3 IPS |
|
|
Image Classification (HP)
|
100% |
2297
427.2 IPS |
|
|
Image Classification (Q)
|
96% |
1693
316.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1700
27.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2641
42.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
3037
49.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
13008
15.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
25317
29.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
19726
23.1 IPS |
|
|
Object Detection (SP)
|
100% |
1671
132.6 IPS |
|
|
Object Detection (HP)
|
97% |
2718
216.4 IPS |
|
|
Object Detection (Q)
|
94% |
2032
162.0 IPS |
|
|
Face Detection (SP)
|
100% |
3595
42.7 IPS |
|
|
Face Detection (HP)
|
100% |
5805
69.0 IPS |
|
|
Face Detection (Q)
|
100% |
3551
42.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6310
48.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
12231
94.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
8218
64.2 IPS |
|
|
Style Transfer (SP)
|
100% |
24949
32.1 IPS |
|
|
Style Transfer (HP)
|
100% |
39300
50.5 IPS |
|
|
Style Transfer (Q)
|
96% |
29768
38.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5106
188.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6925
255.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4449
164.3 IPS |
|
|
Text Classification (SP)
|
100% |
2299
3.07 KIPS |
|
|
Text Classification (HP)
|
100% |
3965
5.29 KIPS |
|
|
Text Classification (Q)
|
93% |
3946
5.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
4655
80.2 IPS |
|
|
Machine Translation (HP)
|
98% |
6299
108.8 IPS |
|
|
Machine Translation (Q)
|
98% |
6311
109.1 IPS |
