MacBook Pro (14-inch, 2021)
Geekbench ML Score
8104
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 07:02 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.0 (Build 24A5298h) |
| Model | MacBook Pro (14-inch, 2021) |
| Model ID | MacBookPro18,4 |
| Motherboard | MacBookPro18,4 |
| CPU Information | |
|---|---|
| Name | Apple M1 Max |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M1 Max |
| Base Frequency | 3.22 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 | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4354
814.7 IPS |
|
|
Image Classification (F16)
|
100% |
4398
822.9 IPS |
|
|
Image Classification (I8)
|
99% |
3692
690.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1556
26.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1493
24.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1507
25.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
51928
62.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
56026
67.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
53622
64.9 IPS |
|
|
Object Detection (F32)
|
100% |
3450
257.5 IPS |
|
|
Object Detection (F16)
|
100% |
3264
243.7 IPS |
|
|
Object Detection (I8)
|
97% |
3210
239.7 IPS |
|
|
Face Detection (F32)
|
100% |
15088
179.4 IPS |
|
|
Face Detection (F16)
|
98% |
16437
195.4 IPS |
|
|
Face Detection (I8)
|
97% |
13875
165.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
25102
194.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
26432
205.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
23605
183.1 IPS |
|
|
Style Transfer (F32)
|
100% |
87240
114.8 IPS |
|
|
Style Transfer (F16)
|
100% |
98341
129.4 IPS |
|
|
Style Transfer (I8)
|
100% |
98667
129.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12509
446.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12521
447.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
11476
409.8 IPS |
|
|
Text Classification (F32)
|
100% |
2086
3.00 KIPS |
|
|
Text Classification (F16)
|
100% |
3518
5.06 KIPS |
|
|
Text Classification (I8)
|
96% |
3500
5.03 KIPS |
|
|
Machine Translation (F32)
|
100% |
863
15.9 IPS |
|
|
Machine Translation (F16)
|
100% |
887
16.3 IPS |
|
|
Machine Translation (I8)
|
99% |
812
14.9 IPS |
