MacBook Pro (16-inch, 2021)
Geekbench ML Score
7580
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 17 2024 02:34 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B5024e) |
| Model | MacBook Pro (16-inch, 2021) |
| Model ID | MacBookPro18,2 |
| Motherboard | MacBookPro18,2 |
| CPU Information | |
|---|---|
| Name | Apple M1 Max |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M1 Max |
| Base Frequency | 3.21 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 2 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3887
727.4 IPS |
|
|
Image Classification (F16)
|
100% |
3957
740.5 IPS |
|
|
Image Classification (I8)
|
99% |
3510
656.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1496
25.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1504
25.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1428
23.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
51100
61.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
53975
65.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
51235
62.0 IPS |
|
|
Object Detection (F32)
|
100% |
3167
236.5 IPS |
|
|
Object Detection (F16)
|
100% |
3363
251.1 IPS |
|
|
Object Detection (I8)
|
97% |
3013
224.9 IPS |
|
|
Face Detection (F32)
|
100% |
13302
158.2 IPS |
|
|
Face Detection (F16)
|
98% |
15190
180.6 IPS |
|
|
Face Detection (I8)
|
97% |
14190
168.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
23200
179.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
24867
192.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
22110
171.5 IPS |
|
|
Style Transfer (F32)
|
100% |
81331
107.0 IPS |
|
|
Style Transfer (F16)
|
100% |
87837
115.5 IPS |
|
|
Style Transfer (I8)
|
100% |
90660
119.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
11102
396.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11790
421.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
9981
356.4 IPS |
|
|
Text Classification (F32)
|
100% |
2072
2.98 KIPS |
|
|
Text Classification (F16)
|
100% |
3456
4.97 KIPS |
|
|
Text Classification (I8)
|
96% |
3484
5.01 KIPS |
|
|
Machine Translation (F32)
|
100% |
807
14.9 IPS |
|
|
Machine Translation (F16)
|
100% |
802
14.8 IPS |
|
|
Machine Translation (I8)
|
99% |
626
11.5 IPS |
